DeepAI AI Chat
Log In Sign Up

Ensemble Framework for Real-time Decision Making

by   Philip Rodgers, et al.
University of Strathclyde

This paper introduces a new framework for real-time decision making in video games. An Ensemble agent is a compound agent composed of multiple agents, each with its own tasks or goals to achieve. Usually when dealing with real-time decision making, reactive agents are used; that is agents that return a decision based on the current state. While reactive agents are very fast, most games require more than just a rule-based agent to achieve good results. Deliberative agents---agents that use a forward model to search future states---are very useful in games with no hard time limit, such as Go or Backgammon, but generally take too long for real-time games. The Ensemble framework addresses this issue by allowing the agent to be both deliberative and reactive at the same time. This is achieved by breaking up the game-play into logical roles and having highly focused components for each role, with each component disregarding anything outwith its own role. Reactive agents can be used where a reactive agent is suited to the role, and where a deliberative approach is required, branching is kept to a minimum by the removal of all extraneous factors, enabling an informed decision to be made within a much smaller time-frame. An Arbiter is used to combine the component results, allowing high performing agents to be created from simple, efficient components.


The Design Of "Stratega": A General Strategy Games Framework

Stratega, a general strategy games framework, has been designed to foste...

Embracing AWKWARD! Real-time Adjustment of Reactive Plans Using Social Norms

This paper presents the AWKWARD architecture for the development of hybr...

Human strategic decision making in parametrized games

Many real-world games contain parameters which can affect payoffs, actio...

Real-Time BDI Agents: a model and its implementation

The BDI model proved to be effective for developing applications requiri...

Reasoning in Highly Reactive Environments

The aim of my Ph.D. thesis concerns Reasoning in Highly Reactive Environ...

Crippling Crypto-Ransomware

This research seeks to expose a major weakness in Crypto-ransomware by m...

Predicting Enemy's Actions Improves Commander Decision-Making

The Defense Advanced Research Projects Agency (DARPA) Real-time Adversar...