Preface to the special issue: Adaptive Learning Agents, Part 1

An Adaptive Learning Agent is capable of adapting its behaviour in order to react to changes in its environment and using previous experience to improve its performance with respect to some evaluation measure. The community of Adaptive Learning Agents studies systems that are capable of acting autonomously and adapting to their surroundings.While the development of a single learning agent may already present a serious challenge, current research frontiers also have a large focus on systems where multiple agents interact in a shared environment. Often systems are inherently decentralized, and a centralized, single-agent learning approach is not feasible. Examples of such systems can be found in multi-robot set-ups, decentralized network routing, distributed load-balancing, electronic auctions, traffic control and many others.In multiagent settings, agents not only have to deal with a dynamic environment, but also with other agents that act, learn and change over time. When agent objectives are aligned and all agents try to achieve a common goal, coordination among the agents is still required to reach optimal results. When agents have opposing goals, a clear optimal solution may no longer exist and an equilibrium between agents is generally sought. These issues have given rise to an important research track studying coordination mechanisms in multiagent learning.This special issue contains selected papers from the 2013 Adaptive and Learning Agents (ALA) workshop, held as a satellite workshop at the Autonomous Agents and MultiAgent Systems conference in St Pauls, MN, USA. The goal of the ALA workshop is to increase awareness and interest in adaptive agent research, encourage collaboration, and provide a representative overview of current research in the area of Adaptive Learning Agents. It aims at bringing together not only different areas of computer science (e.g. agent architectures, reinforcement learning, and evolutionary algorithms), but also different fields studying similar concepts (e.g. game theory, bio-inspired control, and mechanism design). The workshop serves as an interdisciplinary forum for the discussion of ongoing or completed work in ALA and multiagent systems.