Relevant bibliographies by topics / Reasoning about actions and change

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Reasoning about actions and change'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Reasoning about actions and change"

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Hadjisoteriou, E., and A. Kakas. "Reasoning about actions and change in argumentation." Argument & Computation 6, no. 3 (September 2, 2015): 265–91. http://dx.doi.org/10.1080/19462166.2015.1123774.

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Hunter, A., and J. P. Delgrande. "Iterated Belief Change Due to Actions and Observations." Journal of Artificial Intelligence Research 40 (January 30, 2011): 269–304. http://dx.doi.org/10.1613/jair.3132.

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In action domains where agents may have erroneous beliefs, reasoning about the effects of actions involves reasoning about belief change. In this paper, we use a transition system approach to reason about the evolution of an agent's beliefs as actions are executed. Some actions cause an agent to perform belief revision while others cause an agent to perform belief update, but the interaction between revision and update can be non-elementary. We present a set of rationality properties describing the interaction between revision and update, and we introduce a new class of belief change operators for reasoning about alternating sequences of revisions and updates. Our belief change operators can be characterized in terms of a natural shifting operation on total pre-orderings over interpretations. We compare our approach with related work on iterated belief change due to action, and we conclude with some directions for future research.
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Lifschitz, Vladimir. "Guest editor's introduction: Reasoning about action and change." Journal of Logic Programming 31, no. 1-3 (April 1997): 1–2. http://dx.doi.org/10.1016/s0743-1066(96)00139-2.

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Varzinczak, I. J. "On Action Theory Change." Journal of Artificial Intelligence Research 37 (February 27, 2010): 189–246. http://dx.doi.org/10.1613/jair.2959.

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As historically acknowledged in the Reasoning about Actions and Change community, intuitiveness of a logical domain description cannot be fully automated. Moreover, like any other logical theory, action theories may also evolve, and thus knowledge engineers need revision methods to help in accommodating new incoming information about the behavior of actions in an adequate manner. The present work is about changing action domain descriptions in multimodal logic. Its contribution is threefold: first we revisit the semantics of action theory contraction proposed in previous work, giving more robust operators that express minimal change based on a notion of distance between Kripke-models. Second we give algorithms for syntactical action theory contraction and establish their correctness with respect to our semantics for those action theories that satisfy a principle of modularity investigated in previous work. Since modularity can be ensured for every action theory and, as we show here, needs to be computed at most once during the evolution of a domain description, it does not represent a limitation at all to the method here studied. Finally we state AGM-like postulates for action theory contraction and assess the behavior of our operators with respect to them. Moreover, we also address the revision counterpart of action theory change, showing that it benefits from our semantics for contraction.
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Devedzic, Goran, Danijela Milosevic, Lozica Ivanovic, Dragan Adamovic, and Miodrag Manic. "Reasoning with linguistic preferences using NPN logic." Computer Science and Information Systems 7, no. 3 (2010): 511–28. http://dx.doi.org/10.2298/csis090223003d.

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Negative-positive-neutral logic provides an alternative framework for fuzzy cognitive maps development and decision analysis. This paper reviews basic notion of NPN logic and NPN relations and proposes adaptive approach to causality weights assessment. It employs linguistic models of causality weights activated by measurement-based fuzzy cognitive maps? concepts values. These models allow for quasi-dynamical adaptation to the change of concepts values, providing deeper understanding of possible side effects. Since in the real-world environments almost every decision has its consequences, presenting very valuable portion of information upon which we also make our decisions, the knowledge about the side effects enables more reliable decision analysis and directs actions of decision maker.
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SCHUBERT, LENHART K. "Explanation Closure, Action Closure and the Sandewall Test Suite for Reasoning about Change." Journal of Logic and Computation 4, no. 5 (1994): 679–700. http://dx.doi.org/10.1093/logcom/4.5.679.

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GOODAY, JOHN, and ANTONY GALTON. "The Transition Calculus: a high-level formalism for reasoning about action and change." Journal of Experimental & Theoretical Artificial Intelligence 9, no. 1 (January 1997): 51–66. http://dx.doi.org/10.1080/095281397147239.

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Bhansali, S., G. A. Kramer, and T. J. Hoar. "A Principled Approach Towards Symbolic Geometric Constraint Satisfaction." Journal of Artificial Intelligence Research 4 (June 1, 1996): 419–43. http://dx.doi.org/10.1613/jair.292.

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An important problem in geometric reasoning is to find the configuration of a collection of geometric bodies so as to satisfy a set of given constraints. Recently, it has been suggested that this problem can be solved efficiently by symbolically reasoning about geometry. This approach, called degrees of freedom analysis, employs a set of specialized routines called plan fragments that specify how to change the configuration of a set of bodies to satisfy a new constraint while preserving existing constraints. A potential drawback, which limits the scalability of this approach, is concerned with the difficulty of writing plan fragments. In this paper we address this limitation by showing how these plan fragments can be automatically synthesized using first principles about geometric bodies, actions, and topology.
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Dębska, Agnieszka, and Krystyna Komorowska. "Limitations in reasoning about false beliefs in adults: the effect of priming or the curse of knowledge?" Psychology of Language and Communication 17, no. 3 (December 1, 2013): 269–78. http://dx.doi.org/10.2478/plc-2013-0017.

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Abstract Birch & Bloom (2007) suggest that adults’ reasoning about other people’s mental states is influenced by their privileged knowledge about reality. When asked where a person described in a story would search for a missing object, participants tend to judge with higher probability that the person would search in a particular box when they know that the object is indeed in that box. However, the results of that experiment could be an effect of unintended priming in the experimental materials. The increased attention towards the box might be caused by reading about it in the task instructions. In a new version of the experiment, we controlled for this factor by priming different locations in the instructions. The results show that it is unlikely that priming is the source of Birch and Bloom’s observations: only knowledge about reality changed the participants’ strategies in reasoning about the actions of others.
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Rota, Michael W. "Moral Psychology and Social Change: The Case of Abolition." Journal of Interdisciplinary History 49, no. 4 (March 2019): 567–90. http://dx.doi.org/10.1162/jinh_a_01338.

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The examination of a test case, the popular movement to abolish slavery, demonstrates that the insights of recent psychological research about moral judgment and motivated reasoning can contribute to historians’ understanding of why large-scale shifts in cultural values occur. Moral psychology helps to answer the question of why the abolitionist movement arose and flourished when and where it did. Analysis of motivated reasoning and the just-world bias sheds light on the conditions that promoted recognition of the moral wrongfulness of chattel slavery, as well as on the conditions that promoted morally motivated social action. These findings reveal that residents of Great Britain and the northern United States in the eighteenth and nineteenth centuries were in an unusually good position to perceive, and to act on, the moral problems of slavery. Moral psychology is also applicable to other social issues, such as women’s liberation and egalitarianism.
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Dissertations / Theses on the topic "Reasoning about actions and change"

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Jin, Yi. "Belief Change in Reasoning Agents." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2007. http://nbn-resolving.de/urn:nbn:de:swb:14-1169591206666-14311.

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The capability of changing beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. Belief change therefore is one of the central research fields in Artificial Intelligence (AI) for over two decades. In the AI literature, two different kinds of belief change operations have been intensively investigated: belief update, which deal with situations where the new information describes changes of the world; and belief revision, which assumes the world is static. As another important research area in AI, reasoning about actions mainly studies the problem of representing and reasoning about effects of actions. These two research fields are closely related and apply a common underlying principle, that is, an agent should change its beliefs (knowledge) as little as possible whenever an adjustment is necessary. This lays down the possibility of reusing the ideas and results of one field in the other, and vice verse. This thesis aims to develop a general framework and devise computational models that are applicable in reasoning about actions. Firstly, I shall propose a new framework for iterated belief revision by introducing a new postulate to the existing AGM/DP postulates, which provides general criteria for the design of iterated revision operators. Secondly, based on the new framework, a concrete iterated revision operator is devised. The semantic model of the operator gives nice intuitions and helps to show its satisfiability of desirable postulates. I also show that the computational model of the operator is almost optimal in time and space-complexity. In order to deal with the belief change problem in multi-agent systems, I introduce a concept of mutual belief revision which is concerned with information exchange among agents. A concrete mutual revision operator is devised by generalizing the iterated revision operator. Likewise, a semantic model is used to show the intuition and many nice properties of the mutual revision operator, and the complexity of its computational model is formally analyzed. Finally, I present a belief update operator, which takes into account two important problems of reasoning about action, i.e., disjunctive updates and domain constraints. Again, the updated operator is presented with both a semantic model and a computational model.
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Jin, Yi. "Belief Change in Reasoning Agents: Axiomatizations, Semantics and Computations." Doctoral thesis, Technische Universität Dresden, 2006. https://tud.qucosa.de/id/qucosa%3A24983.

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The capability of changing beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. Belief change therefore is one of the central research fields in Artificial Intelligence (AI) for over two decades. In the AI literature, two different kinds of belief change operations have been intensively investigated: belief update, which deal with situations where the new information describes changes of the world; and belief revision, which assumes the world is static. As another important research area in AI, reasoning about actions mainly studies the problem of representing and reasoning about effects of actions. These two research fields are closely related and apply a common underlying principle, that is, an agent should change its beliefs (knowledge) as little as possible whenever an adjustment is necessary. This lays down the possibility of reusing the ideas and results of one field in the other, and vice verse. This thesis aims to develop a general framework and devise computational models that are applicable in reasoning about actions. Firstly, I shall propose a new framework for iterated belief revision by introducing a new postulate to the existing AGM/DP postulates, which provides general criteria for the design of iterated revision operators. Secondly, based on the new framework, a concrete iterated revision operator is devised. The semantic model of the operator gives nice intuitions and helps to show its satisfiability of desirable postulates. I also show that the computational model of the operator is almost optimal in time and space-complexity. In order to deal with the belief change problem in multi-agent systems, I introduce a concept of mutual belief revision which is concerned with information exchange among agents. A concrete mutual revision operator is devised by generalizing the iterated revision operator. Likewise, a semantic model is used to show the intuition and many nice properties of the mutual revision operator, and the complexity of its computational model is formally analyzed. Finally, I present a belief update operator, which takes into account two important problems of reasoning about action, i.e., disjunctive updates and domain constraints. Again, the updated operator is presented with both a semantic model and a computational model.
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Gooday, John M. "A transition-based approach to reasoning about action and change." Thesis, University of Exeter, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260699.

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Lehmann, Helko. "On reasoning about action and change in the Fluent Calculus." Thesis, University of Southampton, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.249592.

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Peng, Taoxin. "A general approach to temporal reasoning about action and change." Thesis, University of Greenwich, 2001. http://gala.gre.ac.uk/6265/.

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Reasoning about actions and change based on common sense knowledge is one of the most important and difficult tasks in the artificial intelligence research area. A series of such tasks are identified which motivate the consideration and application of reasoning formalisms. There follows a discussion of the broad issues involved in modelling time and constructing a logical language. In general, worlds change over time. To model the dynamic world, the ability to predict what the state of the world will be after the execution of a particular sequence of actions, which take time and to explain how some given state change came about, i.e. the causality are basic requirements of any autonomous rational agent. The research work presented herein addresses some of the fundamental concepts and the relative issues in formal reasoning about actions and change. In this thesis, we employ a new time structure, which helps to deal with the so-called intermingling problem and the dividing instant problem. Also, the issue of how to treat the relationship between a time duration and its relative time entity is examined. In addition, some key terms for representing and reasoning about actions and change, such as states, situations, actions and events are formulated. Furthermore, a new formalism for reasoning about change over time is presented. It allows more flexible temporal causal relationships than do other formalisms for reasoning about causal change, such as the situation calculus and the event calculus. It includes effects that start during, immediately after, or some time after their causes, and which end before, simultaneously with, or after their causes. The presented formalism allows the expression of common-sense causal laws at high level. Also, it is shown how these laws can be used to deduce state change over time at low level. Finally, we show that the approach provided here is expressive.
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Varzinczak, Ivan. "What Is a Good Domain Description? Evaluating & Revising Action Theories in Dynamic Logic." Phd thesis, Université Paul Sabatier - Toulouse III, 2006. http://tel.archives-ouvertes.fr/tel-00319220.

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Traditionally, consistency is the only criterion for the quality of a theory in logic-based approaches to reasoning about actions. This work goes beyond that and contributes to the meta-theory of actions by investigating what other properties a good domain description should satisfy. Having Propositional Dynamic Logic (PDL) as background, we state some meta-theoretical postulates
concerning this sore spot. When all postulates are satisfied, we call the action theory modular. We point out the problems that arise when the postulates about modularity are violated, and propose algorithmic checks that can help the designer of an action theory to overcome them. Besides being easier to understand and more elaboration tolerant in McCarthy's sense, modular theories
have interesting computational properties. Moreover, we also propose a framework for updating domain descriptions and show the importance modularity has in action theory change.
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Ingevall, Markus. "Extending the Knowledge Machine." Thesis, Linköping University, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2427.

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This master's thesis deals with a frame-based knowledge representa- tion language and system called The Knowledge Machine (KM), de- veloped by Peter Clark and Bruce Porter at the University of Texas at Austin. The purpose of the thesis is to show a number of ways of changing and extending KM to handle larger classes of reasoning tasks associated with reasoning about actions and change.

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Berreby, Fiona. "Models of Ethical Reasoning." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS137.

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Cette thèse s’inscrit dans le cadre du projet ANR eThicAa, dont les ambitions ont été : de définir ce que sont des agents autonomes éthiques, de produire des représentations formelles des conflits éthiques et de leurs objets (au sein d’un seul agent autonome, entre un agent autonome et le système auquel il appartient, entre un agent autonome et un humain, entre plusieurs agents autonomes) et d’élaborer des algorithmes d’explication pour les utilisateurs humains. L’objet de la thèse plus particulièrement a été d’étudier la modélisation de conflits éthiques au sein d’un seul agent, ainsi que la production d’algorithmes explicatifs. Ainsi, le travail présenté ici décrit l’utilisation de langages de haut niveau dans la conception d’agents autonomes éthiques. Il propose un cadre logique nouveau et modulaire pour représenter et raisonner sur une variété de théories éthiques, sur la base d’une version modifiée du calcul des événements, implémentée en Answer Set Programming. Le processus de prise de décision éthique est conçu comme une procédure en plusieurs étapes, capturée par quatre types de modèles interdépendants qui permettent à l’agent d’évaluer son environnement, de raisonner sur sa responsabilité et de faire des choix éthiquement informés. En particulier, un modèle d’action permet à l’agent de représenter des scénarios et les changements qui s’y déroulent, un modèle causal piste les conséquences des décisions prises dans les scénarios, rendant possible un raisonnement sur la responsabilité et l’imputabilité des agents, un modèle du Bien donne une appréciation de la valeur éthique intrinsèque de finalités ou d’évènements, un modèle du Juste détermine les décisions acceptables selon des circonstances données. Le modèle causal joue ici un rôle central, car il permet d’identifier des propriétés que supposent les relations causales et qui déterminent comment et dans quelle mesure il est possible d’en inférer des attributions de responsabilité. Notre ambition est double. Tout d’abord, elle est de permettre la représentation systématique d’un nombre illimité de processus de raisonnements éthiques, à travers un cadre adaptable et extensible en vertu de sa hiérarchisation et de sa syntaxe standardisée. Deuxièmement, elle est d’éviter l’écueil de certains travaux d’éthique computationnelle qui directement intègrent l’information morale dans l’engin de raisonnement général sans l’expliciter – alimentant ainsi les agents avec des réponses atomiques qui ne représentent pas la dynamique sous-jacente. Nous visons à déplacer de manière globale le fardeau du raisonnement moral du programmeur vers le programme lui-même
This thesis is part of the ANR eThicAa project, which has aimed to define moral autonomous agents, provide a formal representation of ethical conflicts and of their objects (within one artificial moral agent, between an artificial moral agent and the rules of the system it belongs to, between an artificial moral agent and a human operator, between several artificial moral agents), and design explanation algorithms for the human user. The particular focus of the thesis pertains to exploring ethical conflicts within a single agent, as well as designing explanation algorithms. The work presented here investigates the use of high-level action languages for designing such ethically constrained autonomous agents. It proposes a novel and modular logic-based framework for representing and reasoning over a variety of ethical theories, based on a modified version of the event calculus and implemented in Answer Set Programming. The ethical decision-making process is conceived of as a multi-step procedure captured by four types of interdependent models which allow the agent to represent situations, reason over accountability and make ethically informed choices. More precisely, an action model enables the agent to appraise its environment and the changes that take place in it, a causal model tracks agent responsibility, a model of the Good makes a claim about the intrinsic value of goals or events, and a model of the Right considers what an agent should do, or is most justified in doing, given the circumstances of its actions. The causalmodel plays a central role here, because it permits identifying some properties that causal relations assume and that determine how, as well as to what extent, we may ascribe ethical responsibility on their basis. The overarching ambition of the presented research is twofold. First, to allow the systematic representation of an unbounded number of ethical reasoning processes, through a framework that is adaptable and extensible by virtue of its designed hierarchisation and standard syntax. Second, to avoid the pitfall of some works in current computational ethics that too readily embed moralinformation within computational engines, thereby feeding agents with atomic answers that fail to truly represent underlying dynamics. We aim instead to comprehensively displace the burden of moral reasoning from the programmer to the program itself
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Straß, Hannes. "Default Reasoning about Actions." Doctoral thesis, Universitätsbibliothek Leipzig, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-89316.

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Action Theories are versatile and well-studied knowledge representation formalisms for modelling dynamic domains. However, traditional action theories allow only the specification of definite world knowledge, that is, universal rules for which there are no exceptions. When modelling a complex domain for which no complete knowledge can be obtained, axiomatisers face an unpleasant choice: either they cautiously restrict themselves to the available definite knowledge and live with a limited usefulness of the axiomatisation, or they bravely model some general, defeasible rules as definite knowledge and risk inconsistency in the case of an exception for such a rule. This thesis presents a framework for default reasoning in action theories that overcomes these problems and offers useful default assumptions while retaining a correct treatment of default violations. The framework allows to extend action theories with defeasible statements that express how the domain usually behaves. Normality of the world is then assumed by default and can be used to conclude what holds in the domain under normal circumstances. In the case of an exception, the default assumption is retracted, whereby consistency of the domain axiomatisation is preserved.
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Li, Huaming. "Reasoning about actions and plans in artificial intelligence and engineering." Thesis, University of Bristol, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385690.

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Books on the topic "Reasoning about actions and change"

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Reasoning about madness. Oxford: Oxford University Press, 1978.

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C, Reynolds John. Reasoning about arrays. Edinburgh: University of Edinburgh, 1977.

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Reasoning about maddness. New Brunswick [N.J.]: Transaction Publishers, 2009.

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Reasoning and the explanation of actions. Brighton, Sussex: Harvester Press, 1980.

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Collier, William W. Reasoning about parallel architectures. Englewood Cliffs, N. J: Prentice-Hall, 1992.

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Reasoning about theoretical entities. River Edge, N.J: World Scientific Pub., 2003.

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Reasoning about parallel architectures. Englewood Cliffs, N.J: Prentice Hall, 1992.

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Forster, Thomas. Reasoning about theoretical entities. Singapore: World Scientific Pub., 2004.

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Collard, Jean-François, ed. Reasoning About Program Transformations. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/b97654.

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Liu, Fenrong. Reasoning about Preference Dynamics. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1344-4.

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Book chapters on the topic "Reasoning about actions and change"

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Sandewall, Erik. "Reasoning about actions and change with ramification." In Computer Science Today, 486–504. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0015262.

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Łukaszewicz, Witold, and Ewa Madalińska-Bugaj. "Reasoning about action and change: Actions with abnormal effects." In KI-95: Advances in Artificial Intelligence, 209–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60343-3_38.

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Łukaszewicz, Witold, and Ewa Madalińska-Bugaj. "Reasoning about Action and Change: Actions with Abnormal Effects." In Agent-Based Defeasible Control in Dynamic Environments, 399–409. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-1741-0_15.

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Dupin de Saint-Cyr, Florence, Andreas Herzig, Jérôme Lang, and Pierre Marquis. "Reasoning About Action and Change." In A Guided Tour of Artificial Intelligence Research, 487–518. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-06164-7_15.

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Kakas, Antonis, Rob Miller, and Francesca Toni. "An Argumentation Framework for Reasoning about Actions and Change." In Logic Programming and Nonmonotonic Reasoning, 78–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-46767-x_6.

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Dimopoulos, Yannis, Antonis C. Kakas, and Loizos Michael. "Reasoning About Actions and Change in Answer Set Programming." In Logic Programming and Nonmonotonic Reasoning, 61–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24609-1_8.

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LeBlanc, Emily, Marcello Balduccini, and Joost Vennekens. "Explaining Actual Causation via Reasoning About Actions and Change." In Logics in Artificial Intelligence, 231–46. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19570-0_15.

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Nickles, Matthias. "Integrating Relational Reinforcement Learning with Reasoning about Actions and Change." In Inductive Logic Programming, 255–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31951-8_23.

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Jabłonowski, Janusz, Witold Lukaszewicz, and Ewa Madalińska-Bugaj. "Reasoning about action and change: Defeasible observations and actions with abnormal effects." In Lecture Notes in Computer Science, 135–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61708-6_55.

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Dovier, Agostino, Andrea Formisano, and Enrico Pontelli. "Perspectives on Logic-Based Approaches for Reasoning about Actions and Change." In Lecture Notes in Computer Science, 259–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20832-4_17.

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Conference papers on the topic "Reasoning about actions and change"

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Klassen, Toryn Q., Sheila A. McIlraith, and Hector J. Levesque. "Changing Beliefs about Domain Dynamics in the Situation Calculus." In 17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/kr.2020/57.

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Agents change their beliefs about the plausibility of various aspects of domain dynamics -- effects of physical actions, results of sensing, and action preconditions -- as a consequence of their interactions with the world. In this paper we propose a way to conveniently represent domain dynamics in the situation calculus to support such belief change. Furthermore, we suggest patterns to follow when writing the axioms that describe the effects of actions, and prove how these patterns can control the extent to which observations change the agent's beliefs about action effects. We also discuss the relation of our work to the AGM postulates for belief revision. Finally, we show how beliefs about domain dynamics can be incorporated into a form of regression rewriting to support reasoning.
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Belle, Vaishak, and Gerhard Lakemeyer. "Reasoning about Probabilities in Unbounded First-Order Dynamical Domains." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/115.

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When it comes to robotic agents operating in an uncertain world, a major concern in knowledge representation is to better relate high-level logical accounts of belief and action to the low-level probabilistic sensorimotor data. Perhaps the most general formalism for dealing with degrees of belief and, in particular, how such beliefs should evolve in the presence of noisy sensing and acting is the account by Bacchus, Halpern, and Levesque. In this paper, we reconsider that model of belief, and propose a new logical variant that has much of the expressive power of the original, but goes beyond it in novel ways. In particular, by moving to a semantical account of a modal variant of the situation calculus based on possible worlds with unbounded domains and probabilistic distributions over them, we are able to capture the beliefs of a fully introspective knowledge base with uncertainty by way of an only-believing operator. The paper introduces the new logic and discusses key properties as well as examples that demonstrate how the beliefs of a knowledge base change as a result of noisy actions.
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Tandon, Niket, Bhavana Dalvi, Joel Grus, Wen-tau Yih, Antoine Bosselut, and Peter Clark. "Reasoning about Actions and State Changes by Injecting Commonsense Knowledge." In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/d18-1006.

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Claßen, Jens, and James Delgrande. "Dyadic Obligations over Complex Actions as Deontic Constraints in the Situation Calculus." In 17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/kr.2020/26.

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With the advent of artificial agents in everyday life, it is important that these agents are guided by social norms and moral guidelines. Notions of obligation, permission, and the like have traditionally been studied in the field of Deontic Logic, where deontic assertions generally refer to what an agent should or should not do; that is they refer to actions. In Artificial Intelligence, the Situation Calculus is (arguably) the best known and most studied formalism for reasoning about action and change. In this paper, we integrate these two areas by incorporating deontic notions into Situation Calculus theories. We do this by considering deontic assertions as constraints, expressed as a set of conditionals, which apply to complex actions expressed as GOLOG programs. These constraints induce a ranking of "ideality" over possible future situations. This ranking in turn is used to guide an agent in its planning deliberation, towards a course of action that adheres best to the deontic constraints. We present a formalization that includes a wide class of (dyadic) deontic assertions, lets us distinguish prima facie from all-things-considered obligations, and particularly addresses contrary-to-duty scenarios. We furthermore present results on compiling the deontic constraints directly into the Situation Calculus action theory, so as to obtain an agent that respects the given norms, but works solely based on the standard reasoning and planning techniques.
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Balduccini, Marcello, Michael Gelfond, Enrico Pontelli, and Tran Cao Son. "An Answer Set Programming Framework for Reasoning about Agents' Beliefs and Truthfulness of Statements." In 17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/kr.2020/8.

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The paper proposes a framework for capturing how an agent’s beliefs evolve over time in response to observations and for answering the question of whether statements made by a third party can be believed. The basic components of the framework are a formalism for reasoning about actions, changes, and observations and a formalism for default reasoning. The paper describes a concrete implementation that leverages answer set programming for determining the evolution of an agent's ``belief state'', based on observations, knowledge about the effects of actions, and a theory about how these influence an agent's beliefs. The beliefs are then used to assess whether statements made by a third party can be accepted as truthful. The paper investigates an application of the proposed framework in the detection of man-in-the-middle attacks targeting computers and cyber-physical systems. Finally, we briefly discuss related work and possible extensions.
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Fan, Tuan-Fang, and Churn-Jung Liau. "Possibilistic Reasoning About Actions in Agent Systems." In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2018. http://dx.doi.org/10.1109/compsac.2018.00120.

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Barry, M., and R. Watson. "Reasoning about actions for spacecraft redundancy management." In 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403). IEEE, 1999. http://dx.doi.org/10.1109/aero.1999.790194.

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"INTEGRATING REASONING ABOUT ACTIONS AND BAYESIAN NETWORKS." In 2nd International Conference on Agents and Artificial Intelligence. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002724602980304.

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Liu, Yisong, Shan Zhong, Junpeng Wan, and Weihua Wu. "Predicate/Transition Net Based Model for Reasoning about Actions." In 2008 International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2008. http://dx.doi.org/10.1109/iscid.2008.60.

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Kitajima, Natsumi, Yuichi Goto, and Jingde Cheng. "Fast Qualitative Reasoning about Actions for Computing Anticipatory Systems." In 2008 Third International Conference on Availability, Reliability and Security. IEEE, 2008. http://dx.doi.org/10.1109/ares.2008.118.

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Reports on the topic "Reasoning about actions and change"

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Bendixen, Shannon, Michael Campbell, Corey Criswell, and Roland Smith. Change-Capable Leadership The Real Power Propelling Successful Change. Center for Creative Leadership, 2017. http://dx.doi.org/10.35613/ccl.2017.2049.

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If you could ask 275 senior executive leaders about how to lead change, what would they have to say? What if they talked about the most important factors for success, what you should do more of, do less of, or avoid all together? What if their experiences could help you lead change in your organization and provide an early warning system to avoid failure? Do we have your attention? If you are a leader facing complex business challenges in your organization that require changes in the way people have always done things, we offer the following insights from the senior executives we asked about their experiences in leading change: 1. Change yourself. Leading change successfully means spending time outside of your comfort zone. As the individual leading an initiative you must change your mindset, actions, and behaviors. 2. Don’t go it alone. Leading change is a team activity. People come together driven by a compelling, and frequently communicated, message about why we are changing. 3. Know the signs . Recognize the early warning signs that indicate an initiative is starting to derail.
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Qin, Hua, Yanu Prasetyo, Christine Sanders, Elizabeth Prentice, and Muh Syukron. Perceptions and behaviors in response to the novel coronavirus disease 2019 (COVID-19) : reports on major survey findings. University of Missouri, Division of Applied Social Sciences, 2020. http://dx.doi.org/10.32469/10355/79261.

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The United States has been affected by an extensive novel coronavirus (COVID-19) outbreak since March 2020. On March 9, 2020 we started an online survey of people’s perceptions and behaviors related to this issue in Missouri and adjacent states (Kansas, Iowa, Illinois, and Arkansas). The survey was ended on June 9, 2020 and in total 7,392 surveys were completed. In order to assess how attitudes and behaviors related to COVID-19 may change over time, two follow-up surveys were conducted with those respondents who indicated interest in the re-surveys and provided an email address. These two working reports summarize major results of the initial survey and three survey waves, including respondents’ perceived severity of the COVID-19 outbreak, sources of information, knowledge about COVID-19, perceptions of COVID-19 risk, satisfaction with management entities, and preventive actions.
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S. Abdellatif, Omar, Ali Behbehani, and Mauricio Landin. Luxembourg COVID-19 Governmental Response. UN Compliance Research Group, August 2021. http://dx.doi.org/10.52008/lux0501.

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The UN Compliance Research Group is a global organization which specializes in monitoring the work of the United Nations (UN). Through our professional team of academics, scholars, researchers and students we aim to serve as the world's leading independent source of information on members' compliance to UN resolutions and guidelines. Our scope of activity is broad, including assessing the compliance of member states to UN resolutions and plan of actions, adherence to judgments of the International Court of Justice (ICJ), World Health Organization (WHO) guidelines and commitments made at UN pledging conferences. We’re proud to present the international community and global governments with our native research findings on states’ annual compliance with the commitments of the UN and its affiliated agencies. Our goal as world citizens is to foster a global change towards a sustainable future; one which starts with ensuring that the words of delegates are transformed into action and that UN initiatives don’t remain ink on paper. Hence, we offer policy analysis and provide advice on fostering accountability and transparency in UN governance as well as tracing the connection between the UN policy-makers and Non-governmental organizations (NGOs). Yet, we aim to adopt a neutral path and do not engage in advocacy for issues or actions taken by the UN or member states. Acting as such, for the sake of transparency. The UN Compliance Research Group dedicates all its effort to inform the public and scholars about the issues and agenda of the UN and its affiliated agencies.
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Bolstad, Rachel. Opportunities for education in a changing climate: Themes from key informant interviews. New Zealand Council for Educational Research, October 2020. http://dx.doi.org/10.18296/rep.0006.

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How can education in Aotearoa New Zealand respond to climate change? This report, part of our wider education and climate change project, outlines findings from 17 in-depth interviews with individuals with a range of viewpoints about climate change and the role of education. Five priority perspectives are covered: youth (aged 16–25); educators; Māori; Pacific New Zealanders; and people with an academic, education system, or policy perspective. Key findings are: Education offers an important opportunity for diverse children and young people to engage in positive, solutions-focused climate learning and action. Interviewees shared local examples of effective climate change educational practice, but said it was often down to individual teachers, students, and schools choosing to make it a focus. Most interviewees said that climate change needs to be a more visible priority across the education system. The perspectives and examples shared suggest there is scope for growth and development in the way that schools and the wider education system in Aotearoa New Zealand respond to climate change. Interviewees’ experiences suggest that localised innovation and change is possible, particularly when young people and communities are informed about the causes and consequences of climate change, and are engaged with what they can do to make a difference. However, effective responses to climate change are affected by wider systems, societal and political structures, norms, and mindsets. Interviewee recommendations for schools, kura, and other learning settings include: Supporting diverse children and young people to develop their ideas and visions for a sustainable future, and to identify actions they can take to realise that future. Involving children and young people in collective and local approaches, and community-wide responses to climate change. Scaffolding learners to ensure that they were building key knowledge, as well as developing ethical thinking, systems thinking, and critical thinking. Focusing on new career opportunities and pathways in an economic transition to a low-carbon, changed climate future. Getting children and young people engaged and excited about what they can do, rather than disengaged, depressed, or feeling like they have no control of their future.
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