From the 1 of 23 linked papers with an AI index.
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Identifying Informative Environments for Cognition Parameter Inference via Bayesian Experimental Design
Manisha Dubey, Rimvydas Rubavicius, N. Siddharth +1
Computational cognitive modeling seeks to infer latent cognitive mechanisms underlying observed behavior. Bayesian inverse planning provides a principled framework for such inferen…
A Minimal Model of Bounded Trade-Off Screening in Multi-Attribute Choice
Manisha Dubey, Anirban Sarkar, Subramanian Ramamoorthy
Human decision-making often involves choosing between multi-attribute alternatives, yet classical models assume fully compensatory utility aggregation despite evidence that people…
Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics
Leonard Hinckeldey, Elliot Fosong, Rimvydas Rubavicius +6
As embodied autonomous systems capable of assisting humans in daily activities remain a major goal for robotics, efficient and appropriate reinforcement learning (RL) simulation te…
Imperfect World Models are Exploitable
Logan Mondal Bhamidipaty, Esmeralda S. Whitammer, David Abel +2
We propose a novel definition of model exploitation in reinforcement learning. Informally, a world model is exploitable if it implies that one policy should be strictly preferred o…
Towards Human Motion World Models via Executable Behaviour Representations
Rimvydas Rubavicius, Manisha Dubey, N. Siddharth +1
Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion quality. To achieve this, we in…
Learning from Demonstration with Implicit Nonlinear Dynamics Models
Peter David Fagan, Subramanian Ramamoorthy
Learning from Demonstration (LfD) is a useful paradigm for training policies that solve tasks involving complex motions, such as those encountered in robotic manipulation. In pract…