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Towards Learning Ab...
Towards Learning Abstractions via Reinforcement Learning
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- Jergéus, Erik (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Oinonen, Leo Karlsson (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Carlsson, Emil, 1995 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Johansson, Moa, 1981 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2022
- 2022
- English.
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In: CEUR Workshop Proceedings. - 1613-0073. ; 3400, s. 120-126
- Related links:
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Abstract
Subject headings
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- In this paper we take the first steps in studying a new approach to synthesis of efficient communication schemes in multi-agent systems, trained via reinforcement learning. We combine symbolic methods with machine learning, in what is referred to as a neuro-symbolic system. The agents are not restricted to only use initial primitives: reinforcement learning is interleaved with steps to extend the current language with novel higher-level concepts, allowing generalisation and more informative communication via shorter messages. We demonstrate that this approach allow agents to converge more quickly on a small collaborative construction task.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Keyword
- Reinforcement learning
- Multi Agent Systems
- Neuro-Symbolic Systems
- Emergent Communication
Publication and Content Type
- kon (subject category)
- ref (subject category)
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