8 accepted papers
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…
This paper discusses the revenue management (RM) problem to maximize revenue by pricing items or services. One challenge in this problem is that the demand distribution is unknown and varies over time in real applications such as airline and retail industries. In particular, the time-varying demand…
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…
We address the joint task allocation and path planning problem whereby an operator with a fleet of vehicles must assign multiple tasks to each vehicle, while ensuring collision-free paths for them such that the total travel cost is minimized. Instead of sequentially solving the task allocation probl…
With the availability of domain specific historical negotiation data, the practical applications of machine learning techniques can prove to be increasingly effective in the field of automated negotiation. Yet a large portion of the literature focuses on domain independent negotiation and thus pass…
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…