18 citations · 30 across the 12 of their papers we have counts for
15 papers
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…
Can You Improve My Code? Optimizing Programs with Local Search
Fatemeh Abdollahi, Saqib Ameen, Matthew E. Taylor +1
This paper introduces a local search method for improving an existing program with respect to a measurable objective. Program Optimization with Locally Improving Search (POLIS) exp…
Controlling Perceived Emotion in Symbolic Music Generation with Monte Carlo Tree Search
Lucas N. Ferreira, Lili Mou, Jim Whitehead +1
This paper presents a new approach for controlling emotion in symbolic music generation with Monte Carlo Tree Search. We use Monte Carlo Tree Search as a decoding mechanism to stee…
What can we Learn Even From the Weakest? Learning Sketches for Programmatic Strategies
Leandro C. Medeiros, David S. Aleixo, Levi H. S. Lelis
In this paper we show that behavioral cloning can be used to learn effective sketches of programmatic strategies. We show that even the sketches learned by cloning the behavior of…
Policy-Guided Heuristic Search with Guarantees
Laurent Orseau, Levi H. S. Lelis
The use of a policy and a heuristic function for guiding search can be quite effective in adversarial problems, as demonstrated by AlphaGo and its successors, which are based on th…
Computer-Generated Music for Tabletop Role-Playing Games
Lucas N. Ferreira, Levi H. S. Lelis, Jim Whitehead
In this paper we present Bardo Composer, a system to generate background music for tabletop role-playing games. Bardo Composer uses a speech recognition system to translate player…
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
Zaheen Farraz Ahmad, Levi H. S. Lelis, Michael Bowling
Sample-based planning is a powerful family of algorithms for generating intelligent behavior from a model of the environment. Generating good candidate actions is critical to the s…
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…
Iterative Budgeted Exponential Search
Malte Helmert, Tor Lattimore, Levi H. S. Lelis +2
We tackle two long-standing problems related to re-expansions in heuristic search algorithms. For graph search, A* can require expansions, where is the number of sta…
Procedural Generation of Initial States of Sokoban
Dâmaris S. Bento, André G. Pereira, Levi H. S. Lelis
Procedural generation of initial states of state-space search problems have applications in human and machine learning as well as in the evaluation of planning systems. In this pap…
Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees
Laurent Orseau, Levi H. S. Lelis, Tor Lattimore
We introduce and analyze two parameter-free linear-memory tree search algorithms. Under mild assumptions we prove our algorithms are guaranteed to perform only a logarithmic factor…
Single-Agent Policy Tree Search With Guarantees
Laurent Orseau, Levi H. S. Lelis, Tor Lattimore +1
We introduce two novel tree search algorithms that use a policy to guide search. The first algorithm is a best-first enumeration that uses a cost function that allows us to prove a…
Asymmetric Action Abstractions for Multi-Unit Control in Adversarial Real-Time Games
Rubens O. Moraes, Levi H. S. Lelis
Action abstractions restrict the number of legal actions available during search in multi-unit real-time adversarial games, thus allowing algorithms to focus their search on a set…