18 citations · 30 across the 12 of their papers we have counts for
4 papers · 1 filter
Program Synthesis with Best-First Bottom-Up Search
Saqib Ameen, Levi H. S. Lelis
Cost-guided bottom-up search (BUS) algorithms use a cost function to guide the search to solve program synthesis tasks. In this paper, we show that current state-of-the-art cost-gu…
Synthesizing Programmatic Policies with Actor-Critic Algorithms and ReLU Networks
Spyros Orfanos, Levi H. S. Lelis
Programmatically Interpretable Reinforcement Learning (PIRL) encodes policies in human-readable computer programs. Novel algorithms were recently introduced with the goal of handli…
Choosing Well Your Opponents: How to Guide the Synthesis of Programmatic Strategies
Rubens O. Moraes, David S. Aleixo, Lucas N. Ferreira +1
This paper introduces Local Learner (2L), an algorithm for providing a set of reference strategies to guide the search for programmatic strategies in two-player zero-sum games. Pre…
Personalization in Human-AI Teams: Improving the Compatibility-Accuracy Tradeoff
Jonathan Martinez, Kobi Gal, Ece Kamar +1
AI systems that model and interact with users can update their models over time to reflect new information and changes in the environment. Although these updates may improve the ov…