Zobrazeno 1 - 10
of 223
pro vyhledávání: '"Norman, Timothy J"'
Autor:
Birkbeck, John, Sobey, Adam, Cerutti, Federico, Flynn, Katherine Heseltine Hurley, Norman, Timothy J.
Reinforcement learning agents can achieve superhuman performance in static tasks but are costly to train and fragile to task changes. This limits their deployment in real-world scenarios where training experience is expensive or the context changes t
Externí odkaz:
http://arxiv.org/abs/2409.03577
Publikováno v:
ECAI 2024
Future reward estimation is a core component of reinforcement learning agents; i.e., Q-value and state-value functions, predicting an agent's sum of future rewards. Their scalar output, however, obfuscates when or what individual future rewards an ag
Externí odkaz:
http://arxiv.org/abs/2408.08230
Effective communication requires the ability to refer to specific parts of an observation in relation to others. While emergent communication literature shows success in developing various language properties, no research has shown the emergence of s
Externí odkaz:
http://arxiv.org/abs/2406.07277
Recently, there has been an explosion of mobile applications that perform computationally intensive tasks such as video streaming, data mining, virtual reality, augmented reality, image processing, video processing, face recognition, and online gamin
Externí odkaz:
http://arxiv.org/abs/2402.11653
In this paper, we present a novel sequential team selection model in soccer. Specifically, we model the stochastic process of player injury and unavailability using player-specific information learned from real-world soccer data. Monte-Carlo Tree Sea
Externí odkaz:
http://arxiv.org/abs/2402.04898
Multi-Agent Policy Gradient (MAPG) has made significant progress in recent years. However, centralized critics in state-of-the-art MAPG methods still face the centralized-decentralized mismatch (CDM) issue, which means sub-optimal actions by some age
Externí odkaz:
http://arxiv.org/abs/2312.15667
Emergent communication studies the development of language between autonomous agents, aiming to improve understanding of natural language evolution and increase communication efficiency. While temporal aspects of language have been considered in comp
Externí odkaz:
http://arxiv.org/abs/2310.06555
Being able to infer ground truth from the responses of multiple imperfect advisors is a problem of crucial importance in many decision-making applications, such as lending, trading, investment, and crowd-sourcing. In practice, however, gathering answ
Externí odkaz:
http://arxiv.org/abs/2305.08664
In a financial exchange, market impact is a measure of the price change of an asset following a transaction. This is an important element of market microstructure, which determines the behaviour of the market following a trade. In this paper, we firs
Externí odkaz:
http://arxiv.org/abs/2305.07559
Autor:
Everett, Gregory, Beal, Ryan J., Matthews, Tim, Early, Joseph, Norman, Timothy J., Ramchurn, Sarvapali D.
Understanding agent behaviour in Multi-Agent Systems (MAS) is an important problem in domains such as autonomous driving, disaster response, and sports analytics. Existing MAS problems typically use uniform timesteps with observations for all agents.
Externí odkaz:
http://arxiv.org/abs/2302.06569