AIIDE 2006 - PDF Preprint Papers

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AIIDE
2006

180views Artificial Intelligence» more AIIDE 2006»

Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games

14 years 25 days ago

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This paper investigates the challenges posed by the application of reinforcement learning to large-scale strategy games. In this context, we present steps and techniques which syn...

Charles A. G. Madeira, Vincent Corruble, Geber Ram...

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Id	Views	Title	Status

1	180	Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games	claim
2	141	The NERO Video Game	claim
3	127	Dynamic Game Balancing: An Evaluation of User Satisfaction	claim
4	124	AI Wall Building in Empire Earth II	claim
5	123	A Framework for Summarizing Game Experiences as Narratives	claim
6	123	Using Natural Language to Manage NPC Dialog	claim
7	123	The Self Organization of Context for Learning in MultiAgent Games	claim
8	121	CrowdMixer: Multiple Agent Types in Situation-Based Crowd Simulations	claim
9	116	Procedural Level Design for Platform Games	claim
10	113	Improving Collaborative Pathfinding Using Map Abstraction	claim
11	113	Normative Echoes: Use and Manipulation of Player Generated Content by Communities of NPCs	claim
12	108	Incorporating Advice into Neuroevolution of Adaptive Agents	claim
13	108	Lightweight Simulation of Air Traffic Control Using Simple Temporal Networks	claim
14	107	Predicting User Physiological Response for Interactive Environments: An Inductive Approach	claim
15	106	Mixing Story and Simulation in Interactive Narrative	claim
16	106	Building Test Beds for AI with the Q3 Mod Base	claim
17	106	A Guided Performance Interface for Augmenting Social Experiences with an Interactive Animatronic Character	claim
18	100	Goal-Directed Hierarchical Dynamic Scripting for RTS Games	claim
19	94	Biased Cost Pathfinding	claim
20	93	Modeling Self-Adapting and Multicultural Non-Player Characters in Artificial Worlds	claim
21	90	Believable and Reactive Crowds in Next Generation Games	claim
22	90	Incremental Heuristic Search in Games: The Quest for Speed	claim
23	87	Intelligent Tutoring Systems for Commercial Games: The Virtual Combat Training Center Tutor and Simulation	claim
24	86	An Abstraction Framework for Cooperation Among Agents and People in a Virtual World	claim
25	71	A Testbed for Evaluating AI Research Systems in Commercial Games	claim
26	66	Representational Requirements for a Plan Based Approach to Automated Camera Control	claim
27	63	Plausible Environment Reconstruction Using Bayesian Networks	claim

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