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Patttern-Based AI Scripting Using ScriptEase [chapter]

Matthew McNaughton, James Redford, Jonathan Schaeffer, Duane Szafron
2003 Lecture Notes in Computer Science  
In addition to behaviors, the model is being extended to include encounter, dialog, and plot patterns.  ...  In this paper, the ScriptEase model for AI scripting is presented. The model is patterntemplate based, allowing designers to quickly build complex behaviors without doing explicit programming.  ...  In the context of role-playing fantasy games, humans use high-level patterns to describe characters and behaviors.  ... 
doi:10.1007/3-540-44886-1_6 fatcat:amdqupcrnbchpcgbgphmfshoya

A Panorama of Artificial and Computational Intelligence in Games

Georgios N. Yannakakis, Julian Togelius
2015 IEEE Transactions on Computational Intelligence and AI in Games  
agents, AI-assisted game design, general game artificial intelligence and AI in commercial games.  ...  We identify ten main research areas within this field: NPC behavior learning, search and planning, player modeling, games as AI benchmarks, procedural content generation, computational narrative, believable  ...  This research was supported, in part, by the FP7 ICT project C2Learn (project no: 318480).  ... 
doi:10.1109/tciaig.2014.2339221 fatcat:vyni6ub7rbakpi53zlojuhpzym

Believable and Effective AI Agents in Virtual Worlds

Iskander Umarov, Maxim Mozgovoy
2012 International Journal of Gaming and Computer-Mediated Simulations  
The rapid development of complex virtual worlds (most notably, in 3D computer and video games) introduces new challenges for the creation of virtual agents, controlled by artificial intelligence (AI) systems  ...  In this paper, we study current approaches to believability and effectiveness of AI behavior in virtual worlds.  ...  The algorithms, implemented in cognitive architectures, are typically based on psychophysiological models of reasoning, and this fact makes AI-controlled game characters human-like.  ... 
doi:10.4018/jgcms.2012040103 fatcat:gr37lv6cwrdihajr3skstas7qy

Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence

Ryan Paul Badman, Thomas Trenholm Hills, Rei Akaishi
2020 Brain Sciences  
The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements.  ...  Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both  ...  Conflicts of  ... 
doi:10.3390/brainsci10060396 pmid:32575758 fatcat:sccrdt2rdvdbrcdk3x5hmpd5oa

AI-Augmented Behavior Analysis for Children with Developmental Disabilities: Building Towards Precision Treatment [article]

Shadi Ghafghazi, Amarie Carnett, Leslie Neely, Arun Das, Paul Rad
2021 arXiv   pre-print
In this article, we present an AI-Augmented Learning and Applied Behavior Analytics (AI-ABA) platform to provide personalized treatment and learning plans to AUIDD individuals.  ...  By defining systematic experiments along with automated data collection and analysis, AI-ABA can promote self-regulative behavior using reinforcement-based augmented or virtual reality and other mobile  ...  laterization in subjects with ASD can be leveraged to build AI models to predict traits of autism [19] .  ... 
arXiv:2102.10635v2 fatcat:sf457ottmvbqdg532hhkfc4tqe

Embedding Information into Game Worlds to Improve Interactive Intelligence [chapter]

G. Michael Youngblood, Frederick W. P. Heckel, D. Hunter Hale, Priyesh N. Dixit
2011 Artificial Intelligence for Computer Games  
This problem of a lack of rich information suitable for consumption by the game AI often limits the true potential for deeper levels of interaction that are becoming more in-demand by game players.  ...  Current game worlds are visually rich but information poor -particularly poor from the artificial intelligence (AI) point of view.  ...  The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA  ... 
doi:10.1007/978-1-4419-8188-2_2 fatcat:6w6kz4q33fhwrmvhuqapdp3qbm

Affective game engines

Eva Hudlicka
2009 Proceedings of the 4th International Conference on Foundations of Digital Games - FDG '09  
To support these functionalities, the games will need to construct affective models of the players, and include computational models of emotion within the game characters.  ...  To achieve the next leap in the level of engagement and effectiveness, particularly in the arena of serious games, gaming research needs to focus on enhancing the social and affective complexity and realism  ...  COMPUTATIONAL EMOTION MODELING IN GAMING The past 15 years have witnessed a rapid growth in computational models of emotion and affective architectures.  ... 
doi:10.1145/1536513.1536565 dblp:conf/fdg/Hudlicka09 fatcat:t45agrumh5blfmoitki3ssmxg4

The 30-Year Cycle In The AI Debate [article]

Jean-Marie Chauvet
2018 arXiv   pre-print
The rapid changes in these everyday work and entertainment tools have fueled a rising interest in the underlying technology itself; journalists write about AI tirelessly, and companies -- of tech nature  ...  This paper reviews briefly the track-record in AI and Machine Learning and finds this pattern of early dramatic successes, followed by philosophical critique and unexpected difficulties, if not downright  ...  Dreyfus already read definite signs of stagnation in such typical AI research domains as language translation, game playing, pattern recognition, and problem solving.  ... 
arXiv:1810.04053v1 fatcat:ghdlrrvjojaxxbwmn5daz3fkee

Explorations in Player Motivations: Virtual Agents [chapter]

Barbaros Bostan
2010 Lecture Notes in Computer Science  
Creating believable agents with personality is a popular research area in game studies but academic research in this area usually focuses on one facet of personality -for example, only on moods or character  ...  The present study proposes a motivational framework to predict goal-directed behaviour of virtual agents in a computer game and explores the opportunities of using personality inventories based on the  ...  Thus, for any gaming situation, the The probability of the occurrence of a behavior can easily be calculated with the introduction of a random variable that represents the uncertainty in human behavior  ... 
doi:10.1007/978-3-642-15399-0_26 fatcat:dg77seeifvdxtncx7j4xtiwm5u

Implementing Augmented Intelligence In Systems Engineering

Mark Petrotta, Troy Peterson
2019 INCOSE International Symposium  
Combining the best of AI and human capabilities, along with effective human/machine interactions and data visualization, offers the potential for orders-of-magnitude improvements in the speed and quality  ...  This paper will explore the opportunities for artificial intelligence (AI) in the system engineering domain, particularly in ways that unite the unique capabilities of the systems engineer with the AI.  ...  Figure 1 - 1 Growth of chess AI capabilities as measured on the ELO ranking scale of zero-sum games. Human grandmaster performance is shown in dashed-red.  ... 
doi:10.1002/j.2334-5837.2019.00619.x fatcat:pjdta4vgezcvvhcc5dweri2sw4

Advances in Games Technology: Software, Models, and Intelligence

Edmond Prakash, Geoff Brindle, Kevin Jones, Suiping Zhou, Narendra S. Chaudhari, Kok-Wai Wong
2009 Simulation & Gaming  
construction of complex game AI models offline.  ...  First, we propose a generic behavior modeling framework that reflects the major observations on human behavior in daily-life situations.  ...  The authors also thank the students who helped in the development of the prototype games described in this article at Manchester Metropolitan University, UK; Nanyang Technological University, Singapore  ... 
doi:10.1177/1046878109335120 fatcat:zslkv3ehkjacbbjiestjwtimsm

Artificial Intelligence: Are You Sure? Beware of What You Wish! [chapter]

Hugo Miguel da Luz dos Santos
2018 Simulation and Gaming  
if robots are due to replace humans as casino table dealers in the realm of table games.  ...  Looming in the purview of gaming leisure industry is the utmost importance of artificial intelligence (AI).  ...  What is more, do EGMs enhance player's illusion of control as for the outcome of game or bet? EGMs reinforce addictive patterns of gambling behavior.  ... 
doi:10.5772/intechopen.71143 fatcat:sfm6jswozraj3b2uu4segdxugq

Building machines that learn and think like people

Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, Samuel J. Gershman
2016 Behavioral and Brain Sciences  
Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans  ...  Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning  ...  Tom Schaul was very helpful in answering questions regarding the DQN learning curves and Frostbite scoring.  ... 
doi:10.1017/s0140525x16001837 pmid:27881212 fatcat:3fjriprksbhaxpqdcydrhmcjqm

Theory of Minds: Understanding Behavior in Groups Through Inverse Planning [article]

Michael Shum, Max Kleiman-Weiner, Michael L. Littman, Joshua B. Tenenbaum
2019 arXiv   pre-print
Our algorithm rapidly recovers an underlying causal model of how agents relate in spatial stochastic games from just a few observations.  ...  The patterns of inference made by this algorithm closely correspond with human judgments and the algorithm makes the same rapid generalizations that people do.  ...  These abstract reasons generalize in ways that mere patterns of behavior do not.  ... 
arXiv:1901.06085v1 fatcat:ci7hsk6aovg2jldwawutqnqq6e

Theory of Minds: Understanding Behavior in Groups through Inverse Planning

Michael Shum, Max Kleiman-Weiner, Michael L. Littman, Joshua B. Tenenbaum
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Our algorithm rapidly recovers an underlying causal model of how agents relate in spatial stochastic games from just a few observations.  ...  The patterns of inference made by this algorithm closely correspond with human judgments and the algorithm makes the same rapid generalizations that people do.  ...  These abstract reasons generalize in ways that mere patterns of behavior do not.  ... 
doi:10.1609/aaai.v33i01.33016163 fatcat:ljsqi5pl2nhuvlgthneubnrfjy
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