Designing a Cognitive Agent Connector for Complex Environments: A Case Study with StarCraft

Vincent J. Koeman*, Harm J. Griffioen, Danny C. Plenge, Koen V. Hindriks

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


The evaluation of cognitive agent systems, which have been advocated as the next generation model for engineering complex, distributed systems, requires more benchmark environments that offer more features and involve controlling more units. One issue that needs to be addressed time and again is how to create a connector for interfacing cognitive agents with such richer environments. Cognitive agents use knowledge technologies for representing state, their actions and percepts, and for deciding what to do next. Issues such as choosing the right level of abstraction for percepts and action synchronization make it a challenge to design a cognitive agent connector for more complex environments. The leading principle for our design approach to connectors for cognitive agents is that each unit that can be controlled in an environment is mapped onto a single agent. We design a connector for the real-time strategy (RTS) game StarCraft and use it as a case study for establishing a design method for developing connectors for environments. StarCraft is particularly suitable to this end, as AI for an RTS game such as StarCraft requires the design of complicated strategies for coordinating hundreds of units that need to solve a range of challenges including handling both short-term as well as long-term goals. We draw several lessons from how our design evolved and from the use of our connector by over 500 students in two years. Our connector is the first implementation that provides full access for cognitive agents to StarCraft: Brood War.

Original languageEnglish
Title of host publicationEngineering Multi-Agent Systems - 6th International Workshop, EMAS 2018, Revised Selected Papers
EditorsDanny Weyns, Viviana Mascardi, Alessandro Ricci
PublisherSpringer Verlag
Number of pages18
ISBN (Print)9783030256920
Publication statusPublished - 1 Jan 2019
Externally publishedYes
Event6th International Workshop on Engineering Multi-Agent Systems, EMAS 2018 - Stockholm, Sweden
Duration: 14 Jul 201815 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11375 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Workshop on Engineering Multi-Agent Systems, EMAS 2018


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