Multi-agent constrained policy optimisation In this section, we first present a theoretically-justified safe multi-agent policy iteration procedure that leverages multi-agent trust region learning and constraine
Secondly, as approximations to the theoretical solution, we propose two safe multi-agent policy gradient methods: Multi-Agent Constrained Policy Optimisation (MACPO) and MAPPO-Lagrangian. Thirdly, we develop the first three safe MARL benchmarks—Safe Multi-Agent MuJoCo (Safe MAMuJoCo), Safe Multi...
These include: multi-objective weighted constraint satisfaction problems (MO-WCSPs) [141] and Multi-objective Constraint Optimisation Problems (MOCOPs) [97, 99]. Or, in their original paper, the equivalent concept of domination. Although individualised reward shaping implies that each agent receives ...
Recent developments in multi-agent reinforcement learning (MARL) offer a way to address this issue from an optimisation perspective, where agents strive to maximise their utility, eliminating the need for manual rule specification. This learning-focused approach aligns with established economic and ...
(Schulman et al.2015), a method in which the gradient steps are constrained to prevent destructive policy updates. PPO uses first-order optimisation to compute the updates, simplifying the algorithm’s tuning and implementation. In contrast to previous methods, SAC and TD3 are off-policy methods...
integrated H∞ control with the principles of optimal control theory, converting the challenge into the task of identifying a Nash equilibrium point in a two-player zero-sum differential game [21], which is in essence the minimax optimisation problem. It is worth noting that the greatest ...
On-line active reward learning for policy optimisation in spoken dialogue systems. In Proceedings of the 54th annual meeting of the association for computational linguistics. Berlin: Association for Computational Linguistics. Zhi-Hua, Z. (2016). AlphaGo special session: An introduction. Acta Automatica...
The notion of ordering is prevalent not only in the definition of cooperative games and solutions to them, but also in their applications to computationally hard optimization problems such as matching, network optimisation, and scheduling [12,22]. In the context of these applications, the notion ...
Distributed dynamic event-triggered algorithm with positive minimum inter-event time for convex optimisation problem. Int. J. Control 2020. [Google Scholar] [CrossRef] Seyboth, G.S.; Dimarogonas, D.V.; Johansson, K.H.; Frasca, P.; Allgöwer, F. On robust synchronization of heterogeneous...
The policy scheme involves two control signals for the stabilization of the approximation and consensus error of each agent dynamic. To this end, based on the concept of the model predictive control approach, the constrained control laws are designed and updated at each time step. The simulations...