Titlebook: Autonomous Agents and Multiagent Systems. Best and Visionary Papers; AAMAS 2023 Workshops Francesco Amigoni,Arunesh Sinha Conference procee

analogous

Neuro-Symbolic AI + Agent Systems: A First Reflection on?Trends, Opportunities and?Challengest agents. This article is a collection of ideas, opinions, and positions from computer scientists who were invited for a panel discussion at the workshop..This collection is not meant to be comprehensive but is rather intended to stimulate further conversation on the field of “Neuro-Symbolic Multi-A

preservative

Novelty Accommodating Multi-agent Planning in?High Fidelity Simulated Open World’s impact. In this work, we demonstrate that a domain-independent AI agent designed to detect, characterize, and accommodate novelty in smaller-scope physics-based games such as Angry Birds and Cartpole can be adapted to successfully perform and reason with novelty in realistic high-fidelity simulat

失望昨天

PURG

Efficient Graph Matching for Video Indexing,be adapted to tackle it. Our algorithmic innovations notably include a state-augmented DQN-based method for learning stochastic policies, which also applies to the usual fair optimization setting without any preferential treatment. We empirically validate our propositions and analyze the experimental results on several application domains.

ICLE

Efficient Graph Matching for Video Indexing, cooperative multi-agent problem is reduced, allowing for more effective learning. The results suggest that our approach is a promising direction for future research in cooperative MARL, especially in complex and partially observable environments.

白楊魚

Graph Colouring and the Probabilistic Methodes in the BT. Importantly, any successful trace induced by the planners satisfies the corresponding . formula. The usefulness of the approach is demonstrated in two ways: a) exploring the alignment between two planners and . goals, and b) solving a sequential . problem for a . robot.

Noctambulant

Learning Reward Machines in?Cooperative Multi-agent Tasks cooperative multi-agent problem is reduced, allowing for more effective learning. The results suggest that our approach is a promising direction for future research in cooperative MARL, especially in complex and partially observable environments.

EVEN

Plan Generation via?Behavior Trees Obtained from?Goal-Oriented LTLf Formulases in the BT. Importantly, any successful trace induced by the planners satisfies the corresponding . formula. The usefulness of the approach is demonstrated in two ways: a) exploring the alignment between two planners and . goals, and b) solving a sequential . problem for a . robot.

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TRUST

0302-9743 stems, AAMAS 2023, held in London, UK, during May 29–June 2, 2023..The 12 regular papers, 5 best papers and 7 visionary papers, presented were carefully reviewed and selected from a total of more than 110 contributions to the workshops. They focus on emerging topics and new trends in the area of aut