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We propose a pheromone-based traffic management model, which simultaneously optimizes vehicle re-routing and traffic light control. Specifically, each car agent deposits multiple digital pheromone on its route. The road infrastructure agents fuse the ...

It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for ...

Multi-agent systems are widely used in renewable and natural resources management. Multi-agent systems are able to manage the complexity of such systems characterized by a large number of interacting entities with different levels of granularity and ...

Taxi service is an important mode of modern public transportation. However, operated by a large number of self-controlled and profit-driven taxi drivers, taxi systems are quite in efficient and difficult to analyze and regulate. While there has been ...

Teams of mobile robots often need to divide up subtasks efficiently. In spatial domains, a key criterion for doing so may depend on distances between robots and the subtasks' locations. This research considers a specific such criterion, namely how to ...

As the prevalence of autonomous agents grows, so does the number of interactions between these agents. Therefore, it is desirable for these agents to be capable of collaborating without pre-coordination. While past research on ad hoc teamwork has ...

Autonomous Intersection Management (AIM) is a reservation-based intersection control protocol that leverages the capacities of autonomous vehicles to dramatically reduce traffic delay at intersections. AIM was designed for the time when all, or most, of ...

Sustainable energy systems of the future could no longer rely on the current paradigm that energy supply follows demand. Since many of the renewable energy resources do not produce power on demand, there is a need for new market structures that motivate ...

Humans are very good at abstract spatial reasoning, both in the physical world and in virtual settings. For example, gamers controlling mobile agents in virtual environments can quickly identify potential collisions and effect evasive action. In a multi-...

Task allocation is an important topic in multiagent and multi-robot teams. In recent years, there has been much research on the use of auction-based methods to provide a distributed approach to task allocation. Team members bid on tasks based on local ...

In this paper, we investigate a non-cooperative sequential bargaining game for allowing a group of agents agents to partition themselves into non-overlapping coalitions. We focus on the issue of how a player's position on the bargaining agenda affects ...

Agent-based simulation is a valuable tool for validating the theoretical models biologists and ethologists use to explain animal behavior. By automating the process of constructing agent-based models (ABM) directly from observation data we can enable ...

In this paper, we develop a novel algorithm which finds a subset of Pareto front of a Multi-Objective Distributed Constraint Optimization Problem. This algorithm utilizes the Lp-norm method, pseudo-tree, and Dynamic Programming technique. Furthermore, ...

Reinforcement Learning (RL) is widely regarded as a generic and effective technique to learn coordinated behaviours in cooperative multi-agent systems (CMAS), but it suffers from slow convergence speed due to the huge joint action space. Incorporating ...

This paper presents a model of social attitudes for reasoning about the appropriate attitude to express during an interaction. It combines a theoretical approach with a study of a corpus of human-to-human interactions.

Curiosity is an emotional motivation that drives knowledge acquisition in learning context. Studies have shown that curiosity positively influences social learning and a peer learner's curiosity may elicit the curiosity of other learners. Hence, ...

The ability to manipulate social and cultural values in order to achieve one's own goals is a hard-to-teach but profitable skill. In this paper we represent a complex social scenario, the Spanish Steps flower selling scam, using a social calculus ...

We are concerned with the problem of how a collection of agents can decide to share a resource, represented as a unit sized pie. We investigate a simple and natural non-cooperative bargaining protocol for this problem, in which players take it in turns ...

Reducing energy consumption of climate control systems is important in order to reduce human environmental foot-print. We consider a method for an automated agent to provide advice to drivers which will motivate them to reduce the energy consumption of ...