A tutorial at IJCAI 2019, August 10 - August 16, Macau, China

The AI Universe of “Actions”: Agency, Causality, Commonsense and Deception

by Chitta Baral and Tran Cao Son

Description Actions have played an important role in AI from its early days starting from their use in McCarthy’s Situation calculus and in AI planning; but more recently actions have played a crucial role in Pearl’s formulations of causal reasoning and do-calculus, in understanding and acquiring action-centric commonsense knowledge, and in dealing with knowledge goals, such as deception, in multi-agent scenarios. In this tutorial we will cover the story of action and change from Heraclitus’ doctrine (540 BC-480 BC) that “all things are in constant flux”, to its role in the early days of AI and through the development of action languages, and the recent developments with respect to multi-agency, causality, commonsense and deception. We will connect all of these so that various researchers working on particular aspects of actions become aware of the broader picture, thus enhancing the research landscape.

Content Overview: a brief history of action languages  Action languages in single agent environments The action language A, state, and transition function  Extension of A domains with static causal laws, non-deterministic actions, and sensing actions  Golog Action languages and causality  Pearl’s do-calculus  Relationship between Pearl’s do-calculus and action languages  Action languages in multi-agent environments Action language mA*, Kripke structure, update models, and transition function  mA* in epistemic planning  Action languages in commonsense reasoning Commonsense reasoning and actions  The knowledge acquisition task and actions  Open challenges, conclusion, and discussion

About the Authors

• Chitta Baral is a Professor in Computer Science at the Arizona State University with research experience in various sub-fields of Artificial Intelligence (AI) such as Knowledge Representation and Reasoning, Natural Language Under- standing, and Image Understanding; and their applications to Molecular Biology, Health Informatics and Robotics. He is the author of the book “Knowledge Representation, Reasoning and Declarative Problem Solving.” 
• Tran Cao Son is a Professor in Computer Science at New Mexico State University. One of his main research interests is reasoning about actions and changes and its applications in planning, diagnosis, and multi-agent systems. 

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