Evolving opponents for interesting interactive computer games

In this paper we introduce experiments on neuro-evolution mechanisms applied to predator/prey multi-character computer games. Our test-bed is a modified version of the well-known Pac-Man game. By viewing the game from the predators’ (i.e. opponents’) perspective, we attempt off-line to evolve neural-controlled opponents capable of playing effectively against computer-guided fixed strategy players. However, emergent near-optimal behaviors make the game less interesting to play. We therefore discuss the criteria that make a game interesting and, furthermore, we introduce a generic measure of predator/prey computer games’ interest. Given this measure, we present an evolutionary mechanism for opponents that keep learning from a player while playing against it (i.e. on-line) and we demonstrate its efficiency and robustness in increasing and maintaining the game’s interest. Computer game opponents following this on-line learning approach show high adaptability to changing player strategies which provides evidence for the approach’s effectiveness against human players.peer-reviewe

Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm

From formal and practical analysis, we identify new challenges that self-adaptive systems pose to the process of quality assurance. When tackling these, the effort spent on various tasks in the process of software engineering is naturally re-distributed. We claim that all steps related to testing need to become self-adaptive to match the capabilities of the self-adaptive system-under-test. Otherwise, the adaptive system's behavior might elude traditional variants of quality assurance. We thus propose the paradigm of scenario coevolution, which describes a pool of test cases and other constraints on system behavior that evolves in parallel to the (in part autonomous) development of behavior in the system-under-test. Scenario coevolution offers a simple structure for the organization of adaptive testing that allows for both human-controlled and autonomous intervention, supporting software engineering for adaptive systems on a procedural as well as technical level.Comment: 17 pages, published at ISOLA 201

The roles of political skill and intrinsic motivation in performance prediction of adaptive selling

Previous studies have long recognized and examined adaptive selling behavior as an effective selling behavior in current selling situations. Although some studies assumed and revealed moderating factors that affect the effectiveness of adaptive selling behavior, few studies examined an individual’s skill as a moderator on this effect. This study focuses on political skill as a type of skill that has been recently found to have positive effects on sales performance. In addition, this study includes intrinsic motivation as an additional moderator that enables political skill to be invested for effective selling behavior. Our analysis of 249 salespeople and 145 supervisors in a matching sample largely supports our hypotheses that the positive effects of adaptive selling behavior on sales performance are the highest when both political skill and intrinsic motivation are high

Criterion-Related Validity of the Children\u27s Occupational Performance Questionnaire

This study examined concurrent, criterion-related validity of a new measure of occupational performance for children, the Children’s Occupational Performance Questionnaire (COP-Q). The COP-Q is completed by caregivers of children to measure performance in five areas of occupation: Activities of Daily Living, Instrumental Activities of Daily Living, Social Participation, Play/Leisure, and Education/Work. Scores from a sample of children ranging in age from birth to 18 years were correlated with scores from the Vineland Adaptive Behavior Scales-II (VABS), a well-established assessment tool of adaptive behavior that measures similar functional areas as the COP-Q. The results indicated that the COP-Q correlates highly and significantly with the constructs measured by the VABS including social interaction, communication, daily living skills, and to a lesser extent, motor skills. The strong relations between these measures suggest that adaptive behavior and occupational performance address similar constructs, and the results supported the validity of the COP-Q as a measure of occupational performance

Enhanced vaccine control of epidemics in adaptive networks

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to an interaction between the adaptive network rewiring and the vaccine application. Disease extinction rates using vaccination are computed, and orders of magnitude less vaccine application is needed to drive the disease to extinction in an adaptive network than in a static one

Probabilistic structural analysis of adaptive/smart/intelligent space structures

A three-bay, space, cantilever truss is probabilistically evaluated for adaptive/smart/intelligent behavior. For each behavior, the scatter (ranges) in buckling loads, vibration frequencies, and member axial forces are probabilistically determined. Sensitivities associated with uncertainties in the structure, material and load variables that describe the truss are determined for different probabilities. The relative magnitude for these sensitivities are used to identify significant truss variables that control/classify its behavior to respond as an adaptive/smart/intelligent structure. Results show that the probabilistic buckling loads and vibration frequencies increase for each truss classification, with a substantial increase for intelligent trusses. Similarly, the probabilistic member axial forces reduce for adaptive and intelligent trusses and increase for smart trusses

A Boolean complete neural model of adaptive behavior

A multi-layered neural assembly is developed which has the capability of learning arbitrary Boolean functions. Though the model neuron is more powerful than those previously considered, assemblies of neurons are needed to detect non-linearly separable patterns. Algorithms for learning at the neuron and assembly level are described. The model permits multiple output systens to share a common memory. Learned evaluation allows sequences of actions to be organized. Computer simulations demonstrate the capabilities of the model

Adaptive microfoundations for emergent macroeconomics

In this paper we present the basics of a research program aimed at providing microfoundations to macroeconomic theory on the basis of computational agentbased adaptive descriptions of individual behavior. To exemplify our proposal, a simple prototype model of decentralized multi-market transactions is offered. We show that a very simple agent-based computational laboratory can challenge more structured dynamic stochastic general equilibrium models in mimicking comovements over the business cycle.Microfoundations of macroeconomics, Agent-based economics, Adaptive behavior