128,673 research outputs found
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Player agency in interactive narrative: audience, actor & author
The question motivating this review paper is, how can
computer-based interactive narrative be used as a constructivist learn-
ing activity? The paper proposes that player agency can be used to
link interactive narrative to learner agency in constructivist theory,
and to classify approaches to interactive narrative. The traditional
question driving research in interactive narrative is, âhow can an in-
teractive narrative deal with a high degree of player agency, while
maintaining a coherent and well-formed narrative?â This question
derives from an Aristotelian approach to interactive narrative that,
as the question shows, is inherently antagonistic to player agency.
Within this approach, player agency must be restricted and manip-
ulated to maintain the narrative. Two alternative approaches based
on Brechtâs Epic Theatre and Boalâs Theatre of the Oppressed are
reviewed. If a Boalian approach to interactive narrative is taken the
conflict between narrative and player agency dissolves. The question
that emerges from this approach is quite different from the traditional
question above, and presents a more useful approach to applying in-
teractive narrative as a constructivist learning activity
The emergence of information systems: a communication-based theory
An information system is more than just the information technology; it is the system that emerges from the complex interactions and relationships between the information technology and the organization. However, what impact information technology has on an organization and how organizational structures and organizational change influence information technology remains an open question. We propose a theory to explain how communication structures emerge and adapt to environmental changes. We operationalize the interplay of information technology and organization as language communities whose members use and develop domain-specific languages for communication. Our theory is anchored in the philosophy of language. In developing it as an emergent perspective, we argue that information systems are self-organizing and that control of this ability is disseminated throughout the system itself, to the members of the language community. Information technology influences the dynamics of this adaptation process as a fundamental constraint leading to perturbations for the information system. We demonstrate how this view is separated from the entanglement in practice perspective and show that this understanding has far-reaching consequences for developing, managing, and examining information systems
Human-Agent Decision-making: Combining Theory and Practice
Extensive work has been conducted both in game theory and logic to model
strategic interaction. An important question is whether we can use these
theories to design agents for interacting with people? On the one hand, they
provide a formal design specification for agent strategies. On the other hand,
people do not necessarily adhere to playing in accordance with these
strategies, and their behavior is affected by a multitude of social and
psychological factors. In this paper we will consider the question of whether
strategies implied by theories of strategic behavior can be used by automated
agents that interact proficiently with people. We will focus on automated
agents that we built that need to interact with people in two negotiation
settings: bargaining and deliberation. For bargaining we will study game-theory
based equilibrium agents and for argumentation we will discuss logic-based
argumentation theory. We will also consider security games and persuasion games
and will discuss the benefits of using equilibrium based agents.Comment: In Proceedings TARK 2015, arXiv:1606.0729
Building Machines That Learn and Think Like People
Recent progress in artificial intelligence (AI) has renewed interest in
building systems that learn and think like people. 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 humans in some respects. Despite their biological inspiration and
performance achievements, these systems differ from human intelligence in
crucial ways. We review progress in cognitive science suggesting that truly
human-like learning and thinking machines will have to reach beyond current
engineering trends in both what they learn, and how they learn it.
Specifically, we argue that these machines should (a) build causal models of
the world that support explanation and understanding, rather than merely
solving pattern recognition problems; (b) ground learning in intuitive theories
of physics and psychology, to support and enrich the knowledge that is learned;
and (c) harness compositionality and learning-to-learn to rapidly acquire and
generalize knowledge to new tasks and situations. We suggest concrete
challenges and promising routes towards these goals that can combine the
strengths of recent neural network advances with more structured cognitive
models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary
proposals (until Nov. 22, 2016).
https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar
The organization of transactions research with the Trust and Tracing Game
This paper presents empirical results of research on the influence of social aspects on the organization of transactions in the domain of chains and networks. The research method used was a gaming simulation called the Trust and Tracing game in which participants trade commodity goods with a hidden quality attribute. Previous sessions of this gaming simulation identified a list of variables for further investigation (Meijer et al., 2006). The use of gaming simulation as data gathering tool for quantitative research in supply chains and networks is a proof-of-principle. This paper shows results from 27 newly conducted sessions and previously unused data from 3 older sessions. Tests confirmed the use of network and market modes of organization. Pre-existing social relations influenced the course of the action in the sessions. Being socially embedded was not beneficial for the score on the performance indicators money and points. The hypothesized reduction in measurable transaction costs when there was high trust between the participants could not be found. Further analysis revealed that participants are able to suspect cheats in a session based on other factors than tracing. Testing hypotheses with data gathered in a gaming simulation proved feasible. Experiences with the methodology used are discusse
Biases in human behavior
The paper shows that biases in individualâs decision-making may result from the process of mental editing by which subjects produce a ârepresentationâ of the decision problem. During this process, individuals make systematic use of default classifications in order to reduce the short-term memory load and the complexity of symbolic manipulation. The result is the construction of an imperfect mental representation of the problem that nevertheless has the advantage of being simple, and yielding âsatisficingâ decisions. The imperfection origins in a trade-off that exists between the simplicity of representation of a strategy and his efficiency. To obtain simplicity, the strategyâs rules have to be memorized and represented with some degree of abstraction, that allow to drastically reduce their number. Raising the level of abstraction with which a strategyâs rule is represented, means to extend the domain of validity of the rule beyond the field in which the rule has been experimented, and may therefore induce to include unintentionally domains in which the rule is inefficient. Therefore the rise of errors in the mental representation of a problem may be the "natural" effect of the categorization and the identification of the building blocks of a strategy. The biases may be persistent and give rise to lock-in effect, in which individuals remain trapped in sub-optimal strategies, as it is proved by experimental results on stability of sub-optimal strategies in games like Target The Two. To understand why sub-optimal strategies, that embody errors, are locally stable, i.e. cannot be improved by small changes in the rules, it is considered Kauffmanâ NK model, because, among other properties, it shows that if there are interdependencies among the rules of a system, than the system admits many sub-optimal solutions that are locally stable, i.e. cannot be improved by simple mutations. But the fitness function in NK model is a random one, while in our context it is more reasonable to define the fitness of a strategy as efficiency of the program. If we introduce this kind of fitness, then the stability properties of the NK model do not hold any longer: the paper shows that while the elementary statements of a strategy are interdependent, it is possible to achieve an optimal configuration of the strategy via mutations and in consequence the sub-optimal solutions are not locally stable under mutations. The paper therefore provides a different explanation of the existence and stability of suboptimal strategies, based on the difficulty to redefine the sub-problems that constitute the building blocks of the problemâs representation
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