Evolutionary Behavior Tree Approaches for Navigating Platform Games

Nicolau, Miguel; Peŕez-Liebana, Diego; O’Neill, Michael; Brabazon, Anthony

doi:10.1109/tciaig.2016.2543661

Cited by 58 publications

(36 citation statements)

References 28 publications

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“…BTs have also been studied in machine learning applications [7], [8] and details regarding efficient parameter passing was investigated in [9]. Finally, a Modellica implementation of BTs was presented in [18].…”

Section: Introductionmentioning

confidence: 99%

How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees

2017

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Abstract-Behavior Trees (BTs) is a way of organizing the switching structure of a Hybrid Dynamical System (HDS), that was originally introduced in the computer game programming community.In this paper, we analyze how the BT representation increases the modularity of a HDS, and how key system properties are preserved over compositions of such systems, in terms of combining two BTs into a larger one. We also show how BTs can be seen as a generalization of Sequential Behavior Compositions, the Subsumption Architecture and Decisions Trees. These three tools are powerful, but quite different, and the fact that they are unified in a natural way in BTs might be a reason for their popularity in the gaming community. We conclude the paper by giving a set of examples illustrating how the proposed analysis tools can be applied to robot control BTs.

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Section: Introductionmentioning

confidence: 99%

How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees

2017

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“…Behavior Tree has gained great success in game AI [19], [20], and showed substantial possibilities in robotics research [6], [8], [12], [21]. IKBT serves as a proof-of-concept of solving high-cognitive problems with Behavior Tree.…”

Section: Perspectivesmentioning

confidence: 99%

IKBT: Solving Symbolic Inverse Kinematics with Behavior Tree

Zhang¹,

Hannaford²

2019

jair

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Serial robot arms have complicated kinematic equations which must be solved to write effective arm planning and control software (the Inverse Kinematics Problem). Existing software packages for inverse kinematics often rely on numerical methods which have significant shortcomings. Here we report a new symbolic inverse kinematics solver which overcomes the limitations of numerical methods, and the shortcomings of previous symbolic software packages. We integrate Behavior Trees, an execution planning framework previously used for controlling intelligent robot behavior, to organize the equation solving process, and a modular architecture for each solution technique. The system successfully solved, generated a LaTex report, and generated a Python code template for 18 out of 19 example robots of 4-6 DOF. The system is readily extensible, maintainable, and multi-platform with few dependencies. The complete package is available with a Modified BSD license on Github.

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“…To identify the redundant or unnecessary sub-trees they used anti-bloat control technique. In another interesting example in [23], the authors applied Grammatical Evolution to generate different levels of environment for Mario game. A BTs root node is a selector with a variable number of Behavior Block (BB) subtrees, encoding sub-behaviors.…”

Section: Related Workmentioning

confidence: 99%

Automatic Difficulty Management and Testing in Games using a Framework Based on Behavior Trees and Genetic Algorithms

Păduraru

Paduraru

2019

2019 24th International Conference on Engineering of Complex Computer Systems (ICECCS)

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The diversity of agent behaviors is an important topic for the quality of video games and virtual environments in general. Offering the most compelling experience for users with different skills is a difficult task, and usually needs important manual human effort for tuning existing code. This can get even harder when dealing with adaptive difficulty systems. Our papers main purpose is to create a framework that can automatically create behaviors for game agents of different difficulty classes and enough diversity. In parallel with this, a second purpose is to create more automated tests for showing defects in the source code or possible logic exploits with less human effort.Index Terms-behavior tree, genetic algorithms, functional testing, automatic difficulty management.

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Evolutionary Behavior Tree Approaches for Navigating Platform Games

Cited by 58 publications

References 28 publications

How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees

How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees

IKBT: Solving Symbolic Inverse Kinematics with Behavior Tree

Automatic Difficulty Management and Testing in Games using a Framework Based on Behavior Trees and Genetic Algorithms

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