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A generalized multidimensional evaluation framework for player goal recognition

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James LesterAuthors Info & Claims

AIIDE'16: Proceedings of the Twelfth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment

Article No.: 29, Pages 197 - 201

Published: 08 October 2016 Publication History

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Abstract

Recent years have seen a growing interest in player modeling, which supports the creation of player-adaptive digital games. A central problem of player modeling is goal recognition, which aims to recognize players' intentions from observable gameplay behaviors. Player goal recognition offers the promise of enabling games to dynamically adjust challenge levels, perform procedural content generation, and create believable NPC interactions. A growing body of work is investigating a wide range of machine learning-based goal recognition models. In this paper, we introduce GOALIE, a multidimensional framework for evaluating player goal recognition models. The framework integrates multiple metrics for player goal recognition models, including two novel metrics, n-early convergence rate and standardized convergence point. We demonstrate the application of the GOALIE framework with the evaluation of several player goal recognition models, including Markov logic network-based, deep feedforward neural network-based, and long short-term memory network-based goal recognizers on two different educational games. The results suggest that GOALIE effectively captures goal recognition behaviors that are key to next-generation player modeling.

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Cited By

Kleinman EAhmad STeng ZBryant ANguyen THarteveld CSeif El-Nasr M(2020)”And then they died”: Using Action Sequences for Data Driven, Context Aware Gameplay AnalysisProceedings of the 15th International Conference on the Foundations of Digital Games10.1145/3402942.3402962(1-12)Online publication date: 15-Sep-2020
https://dl.acm.org/doi/10.1145/3402942.3402962

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A generalized multidimensional evaluation framework for player goal recognition

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cover image Guide Proceedings

AIIDE'16: Proceedings of the Twelfth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment

October 2016

255 pages

ISBN:978-1-57735-772-8

Copyright © 2016 Association for the Advancement of Artificial Intelligence.

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Association for the Advancement of Artificial Intelligence

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AAAI Press

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Published: 08 October 2016

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Cited By

Kleinman EAhmad STeng ZBryant ANguyen THarteveld CSeif El-Nasr M(2020)”And then they died”: Using Action Sequences for Data Driven, Context Aware Gameplay AnalysisProceedings of the 15th International Conference on the Foundations of Digital Games10.1145/3402942.3402962(1-12)Online publication date: 15-Sep-2020
https://dl.acm.org/doi/10.1145/3402942.3402962

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