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Workshop CBR in Games 2021 : Workshop: Artificial Intelligence in Computer Games using pur or hybrid CBR approaches

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Link: https://sites.google.com/view/iccbr-2021-ws-cbr-in-games/start
 
When Sep 13, 2021 - Sep 16, 2021
Where online on ICCBR 2021
Submission Deadline Jun 13, 2021
Notification Due Jul 4, 2021
Final Version Due Jul 18, 2021
Categories    case-based reasoning   computer games   software agents   machine learning
 

Call For Papers

Artificial intelligence in computer games is a growing topic since many decades in research communities and industry. Computer games are also fascinating laboratory environments for pure and hybrid CBR approaches as they include interactivity, complex situations, evolving scenarios and adaptivity challenges. Pure CBR approaches use only CBR as artificial intelligence method to solve a given problem or challenge, while hybrid CBR approaches uses other machine learning techniques like neural networks or reinforcement learning in combination with CBR. Some games often have a rich and complex environment characterized by a huge search space for which an exact model is difficult to build. Real-time games are very dynamic and requires adaptation to different game situations and provide several challenges for intelligent decision making and planning. Learning during games and evolving an artificial intelligence is also a remarkably interesting and challenging topic. These challenges can be tackled with pure or hybrid CBR approaches.

The ICCBR 2021 workshop “Artificial Intelligence in Computer Games using pure or hybrid CBR approaches” is intended to continue the tradition of past workshops and publications on the topics related to CBR in computer games. It is intended for both academic researchers using games as a testbed for CBR, and hybrid approaches as well as industrial researchers from game developing companies and individuals exploiting CBR and hybrid techniques in game design and development.

We welcome contributions from researchers of all directions on pure and hybrid approaches used in a gaming context. These submissions may include, but are not limited to:

➢ Pure or hybrid Case-based learning in games
➢ Adaptive artificial intelligence using pure or hybrid CBR
➢ Tools and CBR approaches for game design
➢ Path planning in games using pure or hybrid CBR
➢ Case-based agents in games
➢ Hybrid approaches for intelligent behaviour of agents in games
➢ CBR in commercial computer games
➢ Lessons learned about pure and hybrid CBR in computer games
➢ Case-based planning and real-time decision making
➢ Strategy recognition and modeling using pure or hybrid CBR
➢ Opponent modelling using pure or hybrid CBR
➢ Emotional modeling and simulation
➢ Interactive narrative and dialogue planning
➢ Execution management of CBR components in RTS games
➢ Evaluation techniques for pure or hybrid CBR approaches in games
➢ Tools for integration CBR into gaming environments

Authors must submit a paper by the workshop paper deadline, formatted according to the Springer LNCS formatting guidelines. The guidelines can be found here:

https://www.springer.com/gp/authors-editors/conference-proceedings/conference-proceedings-guidelines

Papers (submitted and final) should be no longer than 15 pages including references. Please submit your papers using the EasyChair conference management system. The EasyChair workshop page can be found here:

https://easychair.org/my/conference?conf=iccbr2021#

Papers submitted to other conferences or workshops must state the fact as a footnote on page 1, and please also notify the program co-chairs by email. If a paper will appear in another conference proceedings or journal, it must be withdrawn from the workshop.

Author registration policy
For a paper to appear in the proceedings, at least one of the authors must register for the conference by the camera-ready copy deadline. Papers must be presented by one of the authors at the conference live. There will be no video presentations.

Publication
Proceedings will be published by Springer in the book series Lecture Notes in Computer Science

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