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  1. Artificial Intelligence: Power to the People.Heather M. Roff - 2019 - Ethics and International Affairs 33 (2):127-140.
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  • A Bayesian model of plan recognition.Eugene Charniak & Robert P. Goldman - 1993 - Artificial Intelligence 64 (1):53-79.
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  • Fast and accurate data-driven goal recognition using process mining techniques.Zihang Su, Artem Polyvyanyy, Nir Lipovetzky, Sebastian Sardiña & Nick van Beest - 2023 - Artificial Intelligence 323 (C):103973.
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  • Counterplanning: A strategy-based model of adversary planning in real-world situations.Jaime G. Carbonell - 1981 - Artificial Intelligence 16 (3):295-329.
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  • Reasoning based on categorisation for interpreting and acting: a first approach.Elisabetta Zibetti, Vicenç Quera, Charles Tijus & Francesc Salvador Beltran - 2001 - Mind and Society 2 (2):87-104.
    Taking a detour to reach a goal is intelligent behavior based on making inferences. The main purpose of the present research is to show how such apparently complex behavior can emerge from basic mechanisms such as contextual categorisation and goal attribution when perceiving people. We presentacacia (Action by Contextually Automated Categorising Interactive Agents), a computer model implemented using StarLogo software, grounded in the principles of Artificial Life (Al), capable of simulating the behavior of a group of agents with a goal (...)
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  • Tea With Milk? A Hierarchical Generative Framework of Sequential Event Comprehension.Gina R. Kuperberg - 2021 - Topics in Cognitive Science 13 (1):256-298.
    Inspired by, and in close relation with, the contributions of this special issue, Kuperberg elegantly links event comprehension, production, and learning. She proposes an overarching hierarchical generative framework of processing events enabling us to make sense of the world around us and to interact with it in a competent manner.
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  • Distributed artificial intelligence from a socio-cognitive standpoint: Looking at reasons for interaction. [REVIEW]Maria Miceli, Amedo Cesta & Paola Rizzo - 1995 - AI and Society 9 (4):287-320.
    Distributed Artificial Intelligence (DAI) deals with computational systems where several intelligent components interact in a common environment. This paper is aimed at pointing out and fostering the exchange between DAI and cognitive and social science in order to deal with the issues of interaction, and in particular with the reasons and possible strategies for social behaviour in multi-agent interaction is also described which is motivated by requirements of cognitive plausibility and grounded the notions of power, dependence and help. Connections with (...)
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  • Autonomous agents modelling other agents: A comprehensive survey and open problems.Stefano V. Albrecht & Peter Stone - 2018 - Artificial Intelligence 258 (C):66-95.
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  • A probabilistic plan recognition algorithm based on plan tree grammars.Christopher W. Geib & Robert P. Goldman - 2009 - Artificial Intelligence 173 (11):1101-1132.
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  • The Role of Explanations and Plan Recognition in the Learning of Theatrical Scripts.Helga Noice - 1991 - Cognitive Science 15 (3):425-460.
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  • Artificial Perception of Actions.Robert Thibadeau - 1986 - Cognitive Science 10 (2):117-149.
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  • Interacting Plans.Bertram Bruce & Denis Newman - 1978 - Cognitive Science 2 (3):195-233.
    The paper explores certain phenomena which arise in stories, conversations, and human activity in general when the plans of two individuals are formed and carried out in an interactive situation. A notation system for representing interacting plans is introduced and applied in the analysis of a small portion of “Hansel and Gretel.” The analysis illustrates how a single actor plan can be modified by the needs of cooperative interaction with others and how cooperative interactive episodes can be transformed and used (...)
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  • Towards a process model of human personality traits.Jaime G. Carbonell - 1980 - Artificial Intelligence 15 (1-2):49-74.
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