8 accepted papers
The Pickup-and-Delivery Problem with Time Windows (PDPTW) is a time-constrained variant of the vehicle-routing problem (VRP). Complex time constraints make it difficult to solve using existing NCO methods. In this paper, we present the Feasibility-Aware Masked Transformer (FAM-Trans) specialized for
Automated negotiation, a form of interaction among autonomous agents, plays a central role in multi-agent systems, yet the application of large language model (LLM) in this domain remains underexplored. An LLM can serve as a meta-strategist, adaptively selecting explicit strategies for execution by
This letter addresses the joint task allocation and path planning problem, whereby a fleet of vehicles must be optimally assigned to service multiple given tasks while their planned paths must be collision-free. Such a problem composed of two tightly coupled optimization problems has a high complexi
We propose an automated negotiation for a reinforcement learning agent to adapt the agent to unexpected situations such as demand changes in supply chain management (SCM). Existing studies that consider reinforcement learning and SCM assume a centralized environment where the coordination of chain c…
We proposed a novel dual-process optimization approach for parts collection order and route planning in parts warehouses. Conventional multi-agent parts collection typically uses the vehicle routing problem (VRP), which focuses on minimizing the number of agents and costs. However, the model does no…
This study proposed a novel reward-based negotiating agent strategy using an issue-based represented deep policy network. We compared the negotiation strategies with reinforcement learning (RL) by the tournaments toward heuristics-based champion agents in multi-issue negotiation. A bilateral multi-i…
Previous research on the comprehensive negotiation strategy using deep reinforcement learning (RL) has scalability issues of not performing effectively in the large-sized domains. We improve negotiation strategy via deep RL by considering an issue-based represented deep policy network to deal with m…
This paper addresses the problem of path negotiation among self-interested multirobot operators in shared space. In conventional multirobot path planning problems, most of the research thus far has focused on the coordination and planning of collision-free paths for multiple robots with some common…