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Found 8 papers, 2 papers with code
Formal Methods for Autonomous Systems
Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems.
Encouraging Inferable Behavior for Autonomy: Repeated Bimatrix Stackelberg Games with Observations
As a converse result, we also provide a game where the required number of interactions is lower bounded by a function of the desired inferability loss.
Simulator-Driven Deceptive Control via Path Integral Approach
We study the deception problem in the continuous-state discrete-time stochastic dynamics setting and, using motivations from hypothesis testing theory, formulate a Kullback-Leibler control problem for the synthesis of deceptive policies.
On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples
Under no assumption of independent samples, we provide a high-probability, polynomial sample complexity bound for vanilla model-based off-policy evaluation that requires partial or uniform coverage.
Differential Privacy in Cooperative Multiagent Planning
We synthesize policies that are robust to privacy by reducing the value of the total correlation.
Deceptive Planning for Resource Allocation
We consider a team of autonomous agents that navigate in an adversarial environment and aim to achieve a task by allocating their resources over a set of target locations.
Planning Not to Talk: Multiagent Systems that are Robust to Communication Loss
In this work, we develop joint policies for cooperative multiagent systems that are robust to potential losses in communication.
Entropy Maximization for Markov Decision Processes Under Temporal Logic Constraints
Such a policy minimizes the predictability of the paths it generates, or dually, maximizes the exploration of different paths in an MDP while ensuring the satisfaction of a temporal logic specification.
