activity
20172022
most citedWhat can we Learn Even From the Weakest? Learning Sketches for Programmatic Strategies

3 citations · 5 across the 5 of their papers we have counts for

collaborators

10 papers

cs.AI20223 cited

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…

cs.AI20211 cited

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…

cs.SD2020

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…

cs.AI2020

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…

cs.LG2020

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…

cs.DS2019

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…