Parallel Reinforcement Learning for Traffic Signal Control

AbstractDeveloping Adaptive Traffic Signal Control strategies for efficient urban traffic management is a challenging problem, which is not easily solved. Reinforcement Learning (RL) has been shown to be a promising approach when applied to traffic signal control (TSC) problems. When using RL agents for TSC, difficulties may arise with respect to convergence times and performance. This is especially pronounced on complex intersections with many different phases, due to the increased size of the state action space. Parallel Learning is an emerging technique in RL literature, which allows several learning agents to pool their experiences while learning concurrently on the same problem. Here we present an extension to a leading published work on RL for TSC, which leverages the benefits of Parallel Learning to increase exploration and reduce delay times and queue lengths

South Dublin County Profile (NIRSA) Working Paper Series. No. 14

The main objective of this report is to provide a comprehensive assessment of the current situation in order to assist South Dublin County Development Board in the preparation of its strategy for economic, social and cultural development over the next ten years. The city and environs of Dublin now extend over a very extensive area, exceeding the boundaries of the Dublin administrative units. It represents a complex and dynamic functional entity with roles as both the national capital and the principal international gateway for the country. Since the mid 1990s the old county Dublin has been divided into four units for purposes of public administration, within each of which a City/County Development Board was established in 1999. As each Board is required to prepare a strategy for economic, social and cultural development, the approach adopted here is to provide an analysis that takes account of the wider context while also providing detailed small area analysis for the wards/DEDs of the CDB area

Multi-Agent Credit Assignment in Stochastic Resource Management Games

Multi-Agent Systems (MAS) are a form of distributed intelligence, where multiple autonomous agents act in a common environment. Numerous complex, real world systems have been successfully optimised using Multi-Agent Reinforcement Learning (MARL) in conjunction with the MAS framework. In MARL agents learn by maximising a scalar reward signal from the environment, and thus the design of the reward function directly affects the policies learned. In this work, we address the issue of appropriate multi-agent credit assignment in stochastic resource management games. We propose two new Stochastic Games to serve as testbeds for MARL research into resource management problems: the Tragic Commons Domain and the Shepherd Problem Domain. Our empirical work evaluates the performance of two commonly used reward shaping techniques: Potential-Based Reward Shaping and difference rewards. Experimental results demonstrate that systems using appropriate reward shaping techniques for multi-agent credit assignment can achieve near optimal performance in stochastic resource management games, outperforming systems learning using unshaped local or global evaluations. We also present the first empirical investigations into the effect of expressing the same heuristic knowledge in state- or action-based formats, therefore developing insights into the design of multi-agent potential functions that will inform future work

Dún Laoghaire Rathdown County Profile (NIRSA) Working Paper Series. No. 16

The main objective of this report is to provide a comprehensive assessment of the current situation in order to assist Dún Laoghaire Rathdown County Development Board in the preparation of its strategy for economic, social and cultural development over the next ten years. The city and environs of Dublin now extend over a very extensive area, exceeding the boundaries of the Dublin administrative units. It represents a complex and dynamic functional entity with roles as both the national capital and the principal international gateway for the country. Since the mid 1990s the old county Dublin has been divided into four units for purposes of public administration, within each of which a City/County Development Board was established in 1999. As each Board is required to prepare a strategy for economic, social and cultural development, the approach adopted here is to provide an analysis that takes account of the wider context while also providing detailed small area analysis for the wards/DED’s of the CDB area

Dublin City Profile (Dublin County Borough) (NIRSA) Working Paper Series. No. 15

The main objective of this report is to provide a comprehensive assessment of the current situation in order to assist the City Development Board in the preparation of its strategy for economic, social and cultural development over the next ten years. The city of Dublin now extends over a very extensive area, far exceeding the boundary of Dublin Corporation. It represents a complex and dynamic functional entity with roles as both the national capital and the principal international gateway for the country. Since the early 1990’s the old county Dublin has been divided into four units for purposes of public administration, within each of which a City/County Development Board was established in 1999. As each Board is required to prepare a strategy for economic, social and cultural development, the approach adopted here is to provide an analysis that takes account of the wider context while also providing detailed small area analysis for the wards/DEDs of the CDB area