Action Selection


Action selection is the means by which an agent (either an animal or an autonomous artificial system) determines at any instant what to do next.  For AI developers, action selection is also a key mechanism for integrating the design of intelligent systems.  The term action selection does not imply any conscious or deliberate choice, but is rather a functional description of the process of generating intelligent behaviour.

There are two key questions in action selection:
  • What is being selected?
  • How is it being selected?
Theories of action selection range from completely dynamic models, where there are never any discrete acts being selected but only continuous integrated processes resulting in emergent behaviour, to logic-based strictly-sequential provably-optimal lists of actions referred to as plans.  In natural intelligence, we know that some action selection is performed in a distributed manner. For example some actions are controlled from the spine independently of the brain.  But we also know that complex discrete actions are represented by and can be generated from the activation of single nerve cells.

How action selection works in nature is a core research question for the Artificial models of natural Intelligence (AmonI) group at Bath, while producing AI action selection is one of our core technologies --- see AmonI Software.

These are selected publications that explicitly concern the study of action selection. Full references and a complete list of publications are available on my publications page.

Selected Papers

Books, Special Issues and Proceedings

Further Papers

  • Swen E. Gaudl and Joanna J. Bryson, The Extended Ramp Goal Module : Low-Cost Behaviour Arbitration for Real-Time Controllers based on Biological Models of Dopamine Cells, from the IEEE Conference on Computational Intelligence and Games (CIG) 26-29 August 2014 in Dortmund.
  • Jekaterina Novikova, Leon Watts and I,  The role of emotions in inter-action selection. Interaction Studies, 15 (2), pp. 216-223.
  • Jekaterina Novikova, Swen Gaudl, and I, Emotionally Driven Robot Control Architecture for Human-Robot Interaction, in the proceedings Towards Autonomous Robotic Systems (TAROS 2013), pp. 261-263.  Green open access version.
  • John Grey and I, Procedural Quests: A Focus for Agent Interaction in Role-Playing-Games, in Proceedings of the AISB 2011 Symposium AI & Games.  Final version from March 2011.
  • Structuring Intelligence: The Role of Hierarchy, Modularity and Learning in Generating Intelligent Behaviour, from McFarland, D., Stenning, K. and McGonigle-Chalmers, M. (eds.) The Complex Mind: An Inter-disciplinary Approach, which will come out on Palgrave-MacMillan Autumn 2011.  This is the draft sent to the publisher in March 2010.
  • Cyril Brom, Jakub Gemrot, Michal Bída, Ondrej Burkert, Sam J. Partington and I, POSH Tools for Game Agent Development by Students and Non-Programmers, in the proceedings of  CGAMES06.
  • Cyril Brom and I (2006), Action Selection for Intelligent Systems, published as a European Network for the Advancement of Artificial Cognitive Systems white paper.
  • Integrating Life-Like Action Selection into Cycle-Based Agent Simulation Environments, with Tristan J. Caulfield and Jan Drugowitsch.  Documents BOD/MASON.  In the proceedings of Agent 2005 (2006).
  • Samuel J. Partington and I, The Behavior Oriented Design of an Unreal Tournament Character. A case study of using BOD, presenting a relatively complicated POSH plan.  In the proceedings of Intelligent Virtual Agents 2005.
  • Modular Representations of Cognitive Phenomena in AI, Psychology and Neuroscience (in HTML or PDF) in Visions of Mind, Darryl Davis ed. (2004)
  • Bryson, David Martin, Sheila I. McIlraith, Lynn Andrea Stein, Agent-Based Composite Services in DAML-S: The Behavior-Oriented Design of an Intelligent Semantic Web, in Web Intelligence, Springer 2003. Ning Zhong, Jiming Liu, and Yiyu Yao, eds.
  • Where Should Complexity Go? Cooperation in Complex Agents with Minimal Communication In the proceedings of the First GSFC/JPL Workshop on Radical Agent Concepts (WRAC) (2003).
  • Action Selection for an Artificial Life Model of Social Behavior in Non-Human Primates with Jessica Flack. Three-page abstract presented at  Self-Organization and Evolution of Social Behaviour (2002).
  • Intelligent Control Requires More Structure than the Theory of Event Coding Provides (HTML). Commentary on The Theory of Event Coding: A Framework for Perception and Action Planning by Bernhard Hommel, Jochen Müsseler, Gisa Aschersleben and Wolfgang Prinz, both appeared in Behavioral & Brain Sciences (BBS) 24(5)  (2001).
  • The Study of Sequential and Hierarchical Organisation of Behaviour via Artificial Mechanisms of Action Selection.  MPhil Dissertation: University of Edinburgh, Faculty of Social Sciences (Department of Psychology) 2000
  • Bryson & Lynn Andrea Stein, Architectures and Idioms: Making Progress in Agent Design in pdf (or postscript). ATAL 2000, a chapter in Intelligent Agents VI, the final version is © Springer-Verlag.
  • Cross-Paradigm Analysis of Autonomous Agent Architecture in pdf (or compressed postscript) in the Journal of Experimental and Theoretical Artificial Intelligence (JETAI) 12(2).
  • Agent Architecture as Object Oriented Design, presented in Agent Theories, Architectures and Languages 1997, and published in Intelligent Agents IV by Springer in 1998.
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    Joanna  Bryson
    Last updated July 2016