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8 papers · 2 filters
An Algorithmic Theory of Metacognition in Minds and Machines
Rylan Schaeffer
Humans sometimes choose actions that they themselves can identify as sub-optimal, or wrong, even in the absence of additional information. How is this possible? We present an algor…
Conical Classification For Computationally Efficient One-Class Topic Determination
Sameer Khanna
As the Internet grows in size, so does the amount of text based information that exists. For many application spaces it is paramount to isolate and identify texts that relate to a…
De Re Updates
Michael Cohen, Wen Tang, Yanjing Wang
In this paper, we propose a lightweight yet powerful dynamic epistemic logic that captures not only the distinction between de dicto and de re knowledge but also the distinction be…
Targeted Data Acquisition for Evolving Negotiation Agents
Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar +1
Successful negotiators must learn how to balance optimizing for self-interest and cooperation. Yet current artificial negotiation agents often heavily depend on the quality of the…
Contrastive Reinforcement Learning of Symbolic Reasoning Domains
Gabriel Poesia, WenXin Dong, Noah Goodman
Abstract symbolic reasoning, as required in domains such as mathematics and logic, is a key component of human intelligence. Solvers for these domains have important applications,…
Measurable Monte Carlo Search Error Bounds
John Mern, Mykel J. Kochenderfer
Monte Carlo planners can often return sub-optimal actions, even if they are guaranteed to converge in the limit of infinite samples. Known asymptotic regret bounds do not provide a…