Towards more intelligent adaptive video game agents

This paper provides a computational intelligence perspective on the design of intelligent video game agents. The paper explains why this is an interesting area to research, and outlines the most promising approaches to date, including evolution, temporal difference learning and Monte Carlo Tree Search. Strengths and weaknesses of each approach are identified, and some research directions are outlined that may soon lead to significantly improved video game agents with lower development costs

Evolutionary Mechanics: new engineering principles for the emergence of flexibility in a dynamic and uncertain world

Engineered systems are designed to deftly operate under predetermined conditions yet are notoriously fragile when unexpected perturbations arise. In contrast, biological systems operate in a highly flexible manner; learn quickly adequate responses to novel conditions, and evolve new routines and traits to remain competitive under persistent environmental change. A recent theory on the origins of biological flexibility has proposed that degeneracy—the existence of multi-functional components with partially overlapping functions—is a primary determinant of the robustness and adaptability found in evolved systems. While degeneracy’s contribution to biological flexibility is well documented, there has been little investigation of degeneracy design principles for achieving flexibility in systems engineering. Actually, the conditions that can lead to degeneracy are routinely eliminated in engineering design. With the planning of transportation vehicle fleets taken as a case study, this article reports evidence that degeneracy improves the robustness and adaptability of a simulated fleet towards unpredicted changes in task requirements without incurring costs to fleet efficiency. We find that degeneracy supports faster rates of design adaptation and ultimately leads to better fleet designs. In investigating the limitations of degeneracy as a design principle, we consider decision-making difficulties that arise from degeneracy’s influence on fleet complexity. While global decision-making becomes more challenging, we also find degeneracy accommodates rapid distributed decision-making leading to (near-optimal) robust system performance. Given the range of conditions where favorable short-term and long-term performance outcomes are observed, we propose that degeneracy may fundamentally alter the propensity for adaptation and is useful within different engineering and planning contexts

Dynamic time-linkage problems revisited

Dynamic time-linkage problems (DTPs) are common types of dynamic optimization problems where "decisions that are made now... may influence the maximum score that can be obtained in the future"[3]. This paper contributes to understanding the questions of what are the unknown characteristic of DTPs and how to characterize DTPs. Firstly, based on existing definitions we will introduce a more detailed definition to help characterize DTPs. Secondly, although it is believed that DTPs can be solved to optimality with a perfect prediction method to predict function values [3] [4], in this paper we will discuss a new class of DTPs where even with such a perfect prediction method algorithms might still be deceived and hence will not be able to get the optimal results. We will also propose a benchmark problem to study that particular type of time-linkage problems