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Multi-Agent Intention Recognition and Progression

conference contribution
posted on 2024-11-03, 15:39 authored by Michael Dann, Yuan Yao, Natasha Alechina, Brian Logan, Felipe Meneguzzi, John ThangarajahJohn Thangarajah
For an agent in a multi-agent environment, it is often beneficial to be able to predict what other agents will do next when deciding how to act. Previous work in multi-agent intention scheduling assumes a priori knowledge of the current goals of other agents. In this paper, we present a new approach to multi-agent intention scheduling in which an agent uses online goal recognition to identify the goals currently being pursued by other agents while acting in pursuit of its own goals. We show how online goal recognition can be incorporated into an MCTS-based intention scheduler, and evaluate our approach in a range of scenarios. The results demonstrate that our approach can rapidly recognise the goals of other agents even when they are pursuing multiple goals concurrently, and has similar performance to agents which know the goals of other agents a priori.

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  1. 1.
    ISBN - Is published in 9781956792034 (urn:isbn:9781956792034)
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Start page

91

End page

99

Total pages

9

Outlet

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

Name of conference

Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI 2023)

Publisher

International Joint Conferences on Artificial Intelligence

Place published

United States

Start date

2023-08-19

End date

2023-08-25

Language

English

Former Identifier

2006126429

Esploro creation date

2023-11-17

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