Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Sarkar, Atrisha"'
Autor:
Sarkar, Atrisha, Muresanu, Andrei Ioan, Blair, Carter, Sharma, Aaryam, Trivedi, Rakshit S, Hadfield, Gillian K
Generative agents, which implement behaviors using a large language model (LLM) to interpret and evaluate an environment, has demonstrated the capacity to solve complex tasks across many social and technological domains. However, when these agents in
Externí odkaz:
http://arxiv.org/abs/2405.19328
Autor:
Sarkar, Atrisha, Hadfield, Gillian K.
Although there is mounting empirical evidence for the increase in affective polarization, few mechanistic models can explain its emergence at the population level. The question of how such a phenomenon can emerge from divergent opinions of a populati
Externí odkaz:
http://arxiv.org/abs/2403.06264
A central design problem in game theoretic analysis is the estimation of the players' utilities. In many real-world interactive situations of human decision making, including human driving, the utilities are multi-objective in nature; therefore, esti
Externí odkaz:
http://arxiv.org/abs/2303.07435
Modelling pedestrian behavior is crucial in the development and testing of autonomous vehicles. In this work, we present a hierarchical pedestrian behavior model that generates high-level decisions through the use of behavior trees, in order to produ
Externí odkaz:
http://arxiv.org/abs/2206.01601
In order to enable autonomous vehicles (AV) to navigate busy traffic situations, in recent years there has been a focus on game-theoretic models for strategic behavior planning in AVs. However, a lack of common taxonomy impedes a broader understandin
Externí odkaz:
http://arxiv.org/abs/2109.13367
While there has been an increasing focus on the use of game theoretic models for autonomous driving, empirical evidence shows that there are still open questions around dealing with the challenges of common knowledge assumptions as well as modeling b
Externí odkaz:
http://arxiv.org/abs/2109.09861
A particular challenge for both autonomous and human driving is dealing with risk associated with dynamic occlusion, i.e., occlusion caused by other vehicles in traffic. Based on the theory of hypergames, we develop a novel multi-agent dynamic occlus
Externí odkaz:
http://arxiv.org/abs/2109.09807
Autor:
Sarkar, Atrisha, Czarnecki, Krzysztof
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence, 35(6), 5698-5708 (2021)
With autonomous vehicles (AV) set to integrate further into regular human traffic, there is an increasing consensus on treating AV motion planning as a multi-agent problem. However, the traditional game-theoretic assumption of complete rationality is
Externí odkaz:
http://arxiv.org/abs/2009.10033
Autor:
Ilievski, Marko, Sedwards, Sean, Gaurav, Ashish, Balakrishnan, Aravind, Sarkar, Atrisha, Lee, Jaeyoung, Bouchard, Frédéric, De Iaco, Ryan, Czarnecki, Krzysztof
We explore the complex design space of behaviour planning for autonomous driving. Design choices that successfully address one aspect of behaviour planning can critically constrain others. To aid the design process, in this work we decompose the desi
Externí odkaz:
http://arxiv.org/abs/1908.07931
Autor:
Sarkar, Atrisha, Czarnecki, Krzysztof
Performance evaluation of urban autonomous vehicles requires a realistic model of the behavior of other road users in the environment. Learning such models from data involves collecting naturalistic data of real-world human behavior. In many cases, a
Externí odkaz:
http://arxiv.org/abs/1903.01539