Decentralization of Multiagent Policies by Learning What to Communicate

Effective communication is required for teams of robots to solve sophisticated collaborative tasks. In practice it is typical for both the encoding and semantics of communication to be manually defined by an expert; this is true regardless of whether the behaviors themselves are bespoke, optimization based, or learned. We present an agent architecture and training methodology using neural networks to learn task-oriented communication semantics based on the example of a communication-unaware expert policy. A perimeter defense game illustrates the system's ability to handle dynamically changing numbers of agents and its graceful degradation in performance as communication constraints are tightened or the expert's observability assumptions are broken.Comment: 7 page

Two-Player Reconnaissance Game with Half-Planar Target and Retreat Regions

This paper is concerned with a variation of a pursuit-evasion game called the Reconnaissance game, in which an Intruder attempts to approach a territory of interest (target region) and return to a safe zone (retreat region) in the presence of a faster Defender. The target and retreat regions are taken to be disjoint closed half-planes. The objective of the Intruder is two-fold: 1) minimize the distance between her position and the target region and 2) escape to the retreat region before being captured by the Defender. The Defender, on the other hand, strives to maximize the same distance and, if possible, capture the Intruder outside the retreat region. The game is decomposed into a series of two subgames: a Target game and an Escape game. A closed-form solution to each subgame, including the Value function and state-feedback saddle-point strategies, is derived separately. Furthermore, winning regions and barrier surfaces are constructed analytically. Numerical simulation results are presented to showcase the efficacy of the proposed solutions

The Barrier Surface in the Cooperative Football Differential Game

This paper considers the blocking or football pursuit-evasion differential game. Two pursuers cooperate and try to capture the ball carrying evader as far as possible from the goal line. The evader wishes to be as close as possible to the goal line at the time of capture and, if possible, reach the line. In this paper the solution of the game of kind is provided: The Barrier surface that partitions the state space into two winning sets, one for the pursuer team and one for the evader, is constructed. Under optimal play, the winning team is determined by evaluating the associated Barrier function.Comment: 5 pages, 1 figur

Coordinated Defense Allocation in Reach-Avoid Scenarios with Efficient Online Optimization

In this paper, we present a dual-layer online optimization strategy for defender robots operating in multiplayer reach-avoid games within general convex environments. Our goal is to intercept as many attacker robots as possible without prior knowledge of their strategies. To balance optimality and efficiency, our approach alternates between coordinating defender coalitions against individual attackers and allocating coalitions to attackers based on predicted single-attack coordination outcomes. We develop an online convex programming technique for single-attack defense coordination, which not only allows adaptability to joint states but also identifies the maximal region of initial joint states that guarantees successful attack interception. Our defense allocation algorithm utilizes a hierarchical iterative method to approximate integer linear programs with a monotonicity constraint, reducing computational burden while ensuring enhanced defense performance over time. Extensive simulations conducted in 2D and 3D environments validate the efficacy of our approach in comparison to state-of-the-art approaches, and show its applicability in wheeled mobile robots and quadcopters

Synchronous intercept strategies for a robotic defense-intrusion game with two defenders

We study the defense-intrusion game, in which a single attacker robot tries to reach a stationary target that is protected by two defender robots. We focus on the "synchronous intercept problem", where both robots have to reach the attacker robot synchronously to intercept it. Assume that the attacker robot has the control policy which is based on attraction to the target and repulsion from the defenders, two kinds of synchronous intercept strategies are proposed for the defense-intrusion game, introduced here as Attacker-oriented and Neutral-position-oriented. Theoretical analysis and simulation results show that: (1) the two strategies are able to generate different synchronous intercept patterns: contact intercept pattern and stable non-contact intercept pattern, respectively. (2) The contact intercept pattern allows the defender robots to intercept the attacker robot in finite time, while the stable non-contact intercept pattern generates a periodic attractor that prevents the attack robot from reaching the target for infinite time. There is potential to apply the insights obtained into defense-intrusion in real systems, including aircraft escort and the defense of military targets or territorial boundaries