Search Results for author:
Found 4 papers, 0 papers with code
Designing Behavior Trees from Goal-Oriented LTLf Formulas
Temporal logic can be used to formally specify autonomous agent goals, but synthesizing planners that guarantee goal satisfaction can be computationally prohibitive.
Efficiently Evolving Swarm Behaviors Using Grammatical Evolution With PPA-style Behavior Trees
Evolving swarm behaviors with artificial agents is computationally expensive and challenging.
Predicting Plans and Actions in Two-Player Repeated Games
The obtained results show that the proposed Bayesian approach is well suited for modeling agents in two-player repeated games.
Cooperating with Machines
Here, we combine a state-of-the-art machine-learning algorithm with novel mechanisms for generating and acting on signals to produce a new learning algorithm that cooperates with people and other machines at levels that rival human cooperation in a variety of two-player repeated stochastic games.
