Projects per year
Abstract
In this paper we present an extension of Belief-Desire-Intention agents which can adapt their performance in response to changes in their environment. We consider situations in which the agent’s actions no longer perform as anticipated. Our agents maintain explicit descriptions of the expected behaviour of their actions, are able to track action performance, learn new action descriptions and patch affected plans at runtime. Our main contributions are the underlying theoretical mechanisms for data collection about action performance, the synthesis of new action descriptions from this data and the integration with plan reconfiguration. The mechanisms are supported by a practical implementation to validate the approach.
Original language | English |
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Title of host publication | 20th European Conference of Multi-Agents Systems |
Publisher | Springer Nature |
Pages | 345-362 |
DOIs | |
Publication status | Published - 7 Sept 2023 |
Publication series
Name | Multi-Agent Systems |
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Volume | 14282 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Keywords
- Beliefs-Desires-Intentions
- Action Descriptions
- AI Planning
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Space Systems Research Group
Smith, K. (PI), Roberts, P. (PI), Crisp, N. (PI), Mcgrath, C. (PI), Parslew, B. (CoI), Hollingsworth, P. (CoI), Utyuzhnikov, S. (CoI), Lo, K. C. J. (Researcher), Muirhead, I. (PGR student), Wijacinski, K. (PGR student), Kent, B. (PGR student), Mackintosh, J. (PGR student) & Lopez Pardo, B. (PGR student)
Project: Research
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Robotics and Artificial Intelligence for Nuclear (RAIN)
Lennox, B. (PI), Arvin, F. (CoI), Brown, G. (CoI), Carrasco Gomez, J. (CoI), Da Via, C. (CoI), Furber, S. (CoI), Luján, M. (CoI), Watson, S. (CoI), Watts, S. (CoI) & Weightman, A. (CoI)
2/10/17 → 31/03/22
Project: Research