Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
In this course, we will study human-like artificial agents, that is autonomous intelligent agents situated in a virtual
environment similar to real world that act like humans. The course gives an overview of types of such agents and
their architectures with the emphasis on the problem of action selection. The course also focuses on solving
practical issues related to real-time and partially observable environments.
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Umělé bytosti jsou autonomní inteligentní agenti, kteří jsou situovaní v prostředí podobném přirozenému světu a
kteří se chovají podobně jako lidé nebo zvířata. Přednáška podává přehled typů umělých bytostí a jejich architektur
a blíže se zabývá způsobem jejich řízení a praktickým řešením problémů spojených s částečně pozorovatelným
dynamickým prostředím, které je simulované v reálném čase.
Aim of the course -
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
To give the student an overview about artificial beings as embodied intelligent agents, whose decision-making is subject to the bounded rationality.
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Zprostředkovat studentovi přehled o umělých bytostech jako vtělených inteligentních agentech, jejichž rozhodování probíhá v mezích omezené racionality.
Course completion requirements -
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
To complete the course, the student has to receive a credit from labs by solving assignments and then pass the practical examination.
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Podmínkou zakončení předmětu je získat zápočet za řešení praktických úloh ze cvičení a následně složení prakticky orientované zkoušky.
Literature -
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Bratman, M. (1999). Intention, plans, and practical reason. Center for the Study of Language and Information.
Brooks, A. R.: Intelligence without reason. In: Proceedings of the 1991 International Joint Conference on Artificial Intelligence, Sydney (1991) 569-595
Bryson, J.: Hierarchy and sequence vs. full parallelism in reactive action selection architecture. In: From Animals to Animats (SAB00). MA. MIT Press, Cambridge (2000) 147-156
Černý, M., Plch, T., Marko, M., Ondráček, P., & Brom, C. (2014). Smart Areas: A Modular Approach to Simulation of Daily Life in an Open World Video Game. 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), 703-708.
Fu, D., & Houlette, R. (2004). The Ultimate Guide to FSMs in Games. In S. Rabin (Ed.), AI Game Programming Wisdom (First, Vol. 2, pp. 283-302). Massachusetts, USA: Charles River Media.
Grand, S., Cliff, D., Malhotra, A.: Creatures: Artificial life autonomous software-agents for home entertainment. In: Lewis Johnson, W. (eds.): Proceedings of the First International Conference on Autonomou Agents. ACM press (1997) 22-29
Hindriks KV, (2009). Programming Rational Agents in GOAL, Multi-Agent Programming: Languages and Tools and Applications, Springer US, pages:119-157, isbn: 978-0-387-89298-6
Huber, M. J.: JAM: A BDI-theoretic mobile agent architecture. In: Proceedings of the Third International Conference on Autonomous Agents (Agents'99). Seatle (1999) 236-243
Champandard, A. J. (2008). Behavior Trees for Next-Gen Game AI [Video]. Retrieved from http://aigamedev.com/insider/presentations/behavior-trees [17.5.2017]
Kokko, H.: Modelling for Field Biologists and Other Interesting People. Cambridge University Press (2007)
Laird, J. E., Newell, A., Rosenbloom, P.S.: SOAR: An Architecture for General Intelligence. In: Artificial Intelligence, 33(1) (1987) 1-64
Mateas, M.: Interactive Drama, Art and Artificial Intelligence. Ph.D. Dissertation. Department Computer Science, Carnegie Mellon University (2002) viz též: https://eis-blog.soe.ucsc.edu/2012/02/getting-started-with-abl/
Orkin, J. (2006). Three States and a Plan: The AI of F.E.A.R. In Proceedings of the Game Developers Conference (GDC).
Rao, A. S., & Georgeff, M. P. (1995). BDI Agents: From Theory to Practice. Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), San Francisco, USA, 1995, 312--319.
Rabin, S. (ed.): AI Game Programming Wisdom I - IV, Charles River Media (2002 - 8)
Steve Rabin (ed.). Game AI Pro : collected wisdom of game AI professionals, 2013 (Ch. 6)
Tyrrell, T.: Computational Mechanisms for Action Selection. Ph.D. Dissertation. Centre for Cognitive Science, University of Edinburgh (1993)
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Bratman, M. (1999). Intention, plans, and practical reason. Center for the Study of Language and Information.
Brooks, A. R.: Intelligence without reason. In: Proceedings of the 1991 International Joint Conference on Artificial Intelligence, Sydney (1991) 569-595
Bryson, J.: Hierarchy and sequence vs. full parallelism in reactive action selection architecture. In: From Animals to Animats (SAB00). MA. MIT Press, Cambridge (2000) 147-156
Černý, M., Plch, T., Marko, M., Ondráček, P., & Brom, C. (2014). Smart Areas: A Modular Approach to Simulation of Daily Life in an Open World Video Game. 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), 703-708.
Fu, D., & Houlette, R. (2004). The Ultimate Guide to FSMs in Games. In S. Rabin (Ed.), AI Game Programming Wisdom (First, Vol. 2, pp. 283-302). Massachusetts, USA: Charles River Media.
Grand, S., Cliff, D., Malhotra, A.: Creatures: Artificial life autonomous software-agents for home entertainment. In: Lewis Johnson, W. (eds.): Proceedings of the First International Conference on Autonomou Agents. ACM press (1997) 22-29
Hindriks KV, (2009). Programming Rational Agents in GOAL, Multi-Agent Programming: Languages and Tools and Applications, Springer US, pages:119-157, isbn: 978-0-387-89298-6
Huber, M. J.: JAM: A BDI-theoretic mobile agent architecture. In: Proceedings of the Third International Conference on Autonomous Agents (Agents'99). Seatle (1999) 236-243
Champandard, A. J. (2008). Behavior Trees for Next-Gen Game AI [Video]. Retrieved from http://aigamedev.com/insider/presentations/behavior-trees [17.5.2017]
Kokko, H.: Modelling for Field Biologists and Other Interesting People. Cambridge University Press (2007)
Laird, J. E., Newell, A., Rosenbloom, P.S.: SOAR: An Architecture for General Intelligence. In: Artificial Intelligence, 33(1) (1987) 1-64
Mateas, M.: Interactive Drama, Art and Artificial Intelligence. Ph.D. Dissertation. Department Computer Science, Carnegie Mellon University (2002) viz též: https://eis-blog.soe.ucsc.edu/2012/02/getting-started-with-abl/
Orkin, J. (2006). Three States and a Plan: The AI of F.E.A.R. In Proceedings of the Game Developers Conference (GDC).
Rao, A. S., & Georgeff, M. P. (1995). BDI Agents: From Theory to Practice. Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), San Francisco, USA, 1995, 312--319.
Rabin, S. (ed.): AI Game Programming Wisdom I - IV, Charles River Media (2002 - 8)
Steve Rabin (ed.). Game AI Pro : collected wisdom of game AI professionals, 2013 (Ch. 6)
Tyrrell, T.: Computational Mechanisms for Action Selection. Ph.D. Dissertation. Centre for Cognitive Science, University of Edinburgh (1993)
Teaching methods -
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Frontal teaching during lectures, solving practical problems during labs.
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Frontální výuka při přednáškách, řešení praktických úloh při cvičeních.
Requirements to the exam -
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Demonstrate an ability to apply techniques presented during lectures and demonstrated during practical lessons.
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Schopnost prakticky aplikovat znalost látky prezentované na přednáškách, které byly demonstrovány v rámci cvičení na praktických přííkladech.
Syllabus -
Last update: RNDr. Tomáš Holan, Ph.D. (04.01.2024)
Lecture topics:
1. Taxonomy of artificial beings and their applications: learning simulations, video games, serious games, virtual storytelling, interactive drama, computational ethology.