Solving vehicle routing problem by memetic search with evolutionary multitasking
Vehicle routing problem (VRP) is a well-known NP-hard combinational optimization
problem. In the literature, existing approaches can be generally classified into two …
problem. In the literature, existing approaches can be generally classified into two …
An evolutionary transfer reinforcement learning framework for multiagent systems
In this paper, we present an evolutionary transfer reinforcement learning framework (eTL) for
developing intelligent agents capable of adapting to the dynamic environment of multiagent …
developing intelligent agents capable of adapting to the dynamic environment of multiagent …
Automated design of action advising trigger conditions for multiagent reinforcement learning: a genetic programming-based approach
T Wang, X Peng, T Wang, T Liu, D Xu - Swarm and Evolutionary …, 2024 - Elsevier
Action advising is a popular and effective approach to accelerating independent multiagent
reinforcement learning (MARL), especially for the learning systems that all the agents learn …
reinforcement learning (MARL), especially for the learning systems that all the agents learn …
Evolutionary multiagent transfer learning with model-based opponent behavior prediction
This article embarks a study on multiagent transfer learning (TL) for addressing the specific
challenges that arise in complex multiagent systems where agents have different or even …
challenges that arise in complex multiagent systems where agents have different or even …
Behavior reasoning for opponent agents in multi-agent learning systems
One important component of developing autonomous agents lies in the accurate prediction
of their opponents' behaviors when the agents interact with others in an uncertain …
of their opponents' behaviors when the agents interact with others in an uncertain …
Advances in memetic automaton: Toward human-like autonomous agents in complex multi-agent learning problems
The meme-centric memetic automaton (MA) was recently proposed as an adaptive entity or
a software agent wherein memes are defined as the building blocks of knowledge. The …
a software agent wherein memes are defined as the building blocks of knowledge. The …
Experience sharing based memetic transfer learning for multiagent reinforcement learning
In transfer learning (TL) for multiagent reinforcement learning (MARL), most popular
methods are based on action advising scheme, in which skilled agents directly transfer …
methods are based on action advising scheme, in which skilled agents directly transfer …
Memetic multi-agent optimization in high dimensions using random embeddings
In this paper, we propose a memetic multi-agent optimization (MeMAO) paradigm to
enhance the search efficacy of classical EAs (ie, Differential Evolution (DE)) in solving the …
enhance the search efficacy of classical EAs (ie, Differential Evolution (DE)) in solving the …
SES: a stationary and scalable knowledge transfer approach for multiagent reinforcement learning
T Wang, X Peng, D Xu - Complex & Intelligent Systems, 2021 - Springer
Abstract Knowledge transfer is widely adopted in accelerating multiagent reinforcement
learning (MARL). To accelerate the learning speed of MARL for learning-from scratch …
learning (MARL). To accelerate the learning speed of MARL for learning-from scratch …
[PDF][PDF] Swarm and Evolutionary Computation
abstract This paper proposed a new methodology to determine the optimal trajectory of the
path for multi-robot in a clutter environment using hybridization of improved particle swarm …
path for multi-robot in a clutter environment using hybridization of improved particle swarm …