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  1. 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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  • Expecting the unexpected: Goal recognition for rational and irrational agents.Peta Masters & Sebastian Sardina - 2021 - Artificial Intelligence 297 (C):103490.
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  • Landmark-based approaches for goal recognition as planning.Ramon Fraga Pereira, Nir Oren & Felipe Meneguzzi - 2020 - Artificial Intelligence 279 (C):103217.
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  • Deliberation for autonomous robots: A survey.Félix Ingrand & Malik Ghallab - 2017 - Artificial Intelligence 247 (C):10-44.
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  • (1 other version)Model Based Reasoning in Science and Technology. Logical, Epistemological, and Cognitive Issues.Lorenzo Magnani & Claudia Casadio (eds.) - 2006 - Cham, Switzerland: Springer International Publishing.
    This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. It includes revised contributions presented during the international conference on Model-Based Reasoning (MBR’015), held on June 25-27 in Sestri Levante, Italy. The book is divided into three main parts, the first of which focuses on models, reasoning and representation. It highlights key theoretical concepts from an applied perspective, addressing issues concerning (...)
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  • Belief and truth in hypothesised behaviours.Stefano V. Albrecht, Jacob W. Crandall & Subramanian Ramamoorthy - 2016 - Artificial Intelligence 235 (C):63-94.
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  • Optimizing pathfinding for goal legibility and recognition in cooperative partially observable environments.Sara Bernardini, Fabio Fagnani, Alexandra Neacsu & Santiago Franco - 2024 - Artificial Intelligence 333 (C):104148.
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  • Abduction, Competing Models and the Virtues of Hypotheses.H. G. Callaway - 2010 - In Lorenzo Magnani, Walter Carnielli & Claudio Pizzi (eds.), MODEL-BASED REASONING IN SCIENCE AND TECHNOLOGY. Springer. pp. 263-280.
    This paper focuses on abduction as explicit or readily formulatable inference to possible explanatory hypotheses--as contrasted with inference to conceptual innovations or abductive logic as a cycle of hypotheses, deduction of consequences and inductive testing. Inference to an explanation is often a matter of projection or extrapolation of elements of accepted theory for the solution of outstanding problems in particular domains of inquiry. I say "projections or extrapolation" of accepted theory, but I mean to point to something broader and suggest (...)
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  • The automated understanding of simple bar charts.Stephanie Elzer, Sandra Carberry & Ingrid Zukerman - 2011 - Artificial Intelligence 175 (2):526-555.
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  • Plan recognition in exploratory domains.Yaʼakov Gal, Swapna Reddy, Stuart M. Shieber, Andee Rubin & Barbara J. Grosz - 2012 - Artificial Intelligence 176 (1):2270-2290.
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  • Sequential plan recognition: An iterative approach to disambiguating between hypotheses.Reuth Mirsky, Roni Stern, Kobi Gal & Meir Kalech - 2018 - Artificial Intelligence 260 (C):51-73.
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  • Why bad coffee? Explaining BDI agent behaviour with valuings.Michael Winikoff, Galina Sidorenko, Virginia Dignum & Frank Dignum - 2021 - Artificial Intelligence 300 (C):103554.
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