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  • 1.
    Davidsson, Paul
    et al.
    Blekinge Institute of Technology, Department of Software Engineering and Computer Science.
    Johansson, Stefan J.
    Blekinge Institute of Technology, Department of Software Engineering and Computer Science.
    Evaluating multi-agent system architectures: A case study concerning dynamic resource allocation2003Conference paper (Refereed)
    Abstract [en]

    Much effort has been spent on suggesting and implementing new architectures of Multi-Agent Systems. However, we believe the time has come to compare and evaluate these architectures in a more systematic way. Rather than just studying a particular application, we suggest that more general problem domains corresponding to sets of applications should be studied. Similarly, we argue that it is more useful to study the properties of classes of multi-agent system architectures than particular architectures. Also, it is important to evaluate the architectures in several dimensions, both different performance-related attributes, which are domain dependent and more general quality attributes, such as, robustness, modifiability, and scalability. As a case study we investigate the general problem of "dynamic resource allocation" and present four classes of multi-agent system architectures that solve this problem. These classes are discriminated by their degree of distribution of control and degree of synchronization. Finally, we instantiate each of these architecture classes and evaluate, through simulation experiments, how they solve a concrete dynamic resource allocation problem, namely load balancing and overload control of Intelligent Networks.

  • 2.
    Davidsson, Paul
    et al.
    Blekinge Institute of Technology, School of Computing.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Computing.
    On the Potential of Norm-Governed Behavior in Different Categories of Artificial Societies2006In: Computational and mathematical organization theory, ISSN 1381-298X, E-ISSN 1572-9346, Vol. 12, no 2-3, p. 169-80Article in journal (Refereed)
    Abstract [en]

    Based on a classification of artificial societies and the identification of four different types of stakeholders in such societies, we investigate the potential of norm-governed behavior in different types of artificial societies. The basis of the analysis is the preferences of the stakeholders and how they influence the state of the society. A general conclusion drawn is that the more open a society is the more it has to rely on agent owners and designers to achieve norm-governed behavior, whereas in more closed societies the environment designers and owners may control the degree of norm-governed behavior.

  • 3.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Hilborn, Olle
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Jercic, Petar
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Johansson, Stefan
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Lindley, Craig
    Svensson, Johan
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Wen, Wei
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Psychophysiological Interaction and Empathic Cognition for Human-Robot Cooperative Work (PsyIntEC)2014In: Gearing Up and Accelerating Cross-Fertilization between Academic and Industrial Robotics Research in Europe: Technology Transfer Experiments from the ECHORD Project / [ed] Rohrbein, F.; Veiga, G.; Natale, C., Springer , 2014, p. 283-299Chapter in book (Refereed)
    Abstract [en]

    The aim of the PsyIntEC project is to explore affective and cognitive modeling of humans in human-robot interaction (HRI) as a basis for behavioral adaptation. To achieve this we have explored human affective perception of relevant modalities in human-human and human-robot interaction on a collaborative problem-solving task using psychophysiological measurements. The experiments conducted have given us valuable insight into the communicational and affective queues interplaying in such interactions from the human perspective. The results indicate that there is an increase in both positive and negative emotions when interacting with robots compared to interacting with another human or solving the task alone, but detailed analysis on shorter time segments is required for the results from all sensors to be conclusive and significant.

  • 4.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Computing.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Computing.
    A Multi-agent Potential Field based bot for a Full RTS Game Scenario2009Conference paper (Refereed)
    Abstract [en]

    Computer games in general, and Real Time Strategy games in particular is a challenging task for both AI research and game AI programmers. The player, or AI bot, must use its workers to gather resources. They must be spent wisely on structures such as barracks or factories, mobile units such as soldiers, workers and tanks. The constructed units can be used to explore the game world, hunt down the enemy forces and destroy the opponent buildings. We propose a multi-agent architecture based on artificial potential fields for a full real time strategy scenario. We validate the solution by participating in a yearly open real time strategy game tournament and show that the bot, even though not using any form of path planning for navigation, is able to perform well and win the tournament.

  • 5.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Computing.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Computing.
    A Multiagent Potential Field-Based Bot for Real-Time Strategy Games2009In: International Journal of Computer Games Technology, ISSN 1687-7055, Vol. 2009, article id 910819Article in journal (Refereed)
    Abstract [en]

    Bots for real-time strategy (RTS) games may be very challenging to implement. A bot controls a number of units that will have to navigate in a partially unknown environment, while at the same time avoid each other, search for enemies, and coordinate attacks to fight them down. Potential fields are a technique originating from the area of robotics where it is used in controlling the navigation of robots in dynamic environments. Although attempts have been made to transfer the technology to the gaming sector, assumed problems with efficiency and high costs for implementation have made the industry reluctant to adopt it. We present a multiagent potential field-based bot architecture that is evaluated in two different real-time strategy game settings and compare them, both in terms of performance, and in terms of softer attributes such as configurability with other state of-the-art solutions.We show that the solution is a highly configurable bot that can match the performance standards of traditional RTS bots. Furthermore, we show that our approach deals with Fog of War (imperfect information about the opponent units) surprisingly well.We also show that a multiagent potential field-based bot is highly competitive in a resource gathering scenario.

  • 6.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Computing.
    A Study on Human like Characteristics in Real Time Strategy Games2010Conference paper (Refereed)
    Abstract [en]

    Computer controlled characters (NPCs) are important in any video game to make the game world interesting, give more depth to a game and make the game playable. In almost any game the player has to cooperate with, fight against or interact with NPCs. This is especially true for singleplayer games but NPCs are also important in most multi-player games. When creating NPCs the developers often strive to create human like characters that behave reasonably intelligent in most cases. We have performed a study aiming to give an idea of the characteristics of human like NPCs in real-time strategy (RTS) games. In the study participants were asked to watch a recording of an RTS game and decide and motivate if the players in the game were controlled by a human player or a computer. We recorded matches were human players played against bots as well as bots playing against other bots. The results were categorized into different groups and they showed that some characteristics, for example simultaneous movement, are perceived as very bot-like and other things such as ability to try different tactics are perceived as humanlike.

  • 7.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    Dealing with Fog of War in a Real Time Strategy Game Environment2008Conference paper (Refereed)
    Abstract [en]

    Bots for Real Time Strategy (RTS) games provide a rich challenge to implement. A bot controls a number of units that may have to navigate in a partially unknown environment, while at the same time search for enemies and coordinate attacks to fight them down. It is often the case that RTS AIs cheat in the sense that they get perfect information about the game world to improve the performance of the tactics and planning behavior. We show how a multi-agent potential field based bot can be modified to play an RTS game without cheating, i.e. with incomplete information, and still be able to perform well without spending more resources than its cheating version in a tournament.

  • 8.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Computing.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Computing.
    Measuring player experience on runtime dynamic difficulty scaling in an RTS game2009Conference paper (Refereed)
    Abstract [en]

    Do players find it more enjoyable to win, than to play even matches? We have made a study of what a number of players expressed after playing against computer opponents of different kinds in an RTS game. There were two static computer opponents, one that was easily beaten, and one that was hard to beat, and three dynamic ones that adapted their strength to that of the player. One of these three latter ones intentionally drops its performance in the end of the game to make it easy for the player to win. Our results indicate that the players found it more enjoyable to play an even game against an opponent that adapts to the performance of the player, than playing against an opponent with static difficulty. The results also show that when the computer player that dropped its performance to let the player win was the least enjoyable opponent of them all.

  • 9.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    The Rise of Potential Fields in Real Time Strategy Bots2008Conference paper (Refereed)
    Abstract [en]

    Bots for Real Time Strategy (RTS) games are challenging to implement. A bot controls a number of units that may have to navigate in a partially unknown environment, while at the same time search for enemies and coordinate attacks to fight them down. Potential fields is a technique originating from the area of robotics where it is used in controlling the navigation of robots in dynamic environments. We show that the use of potential fields for implementing a bot for a real time strategy game gives us a very competitive, configurable, and non-conventional solution.

  • 10.
    Hagelbäck, Johan
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    Johansson, Stefan J.
    Blekinge Institute of Technology, School of Engineering, Department of Systems and Software Engineering.
    Using Multi-agent Potential Fields in Real-time Strategy2008Conference paper (Refereed)
    Abstract [en]

    Bots for Real Time Strategy (RTS) games provide a rich challenge to implement. A bot controls a number of units that may have to navigate in a partially unknown environment, while at the same time search for enemies and coordinate attacks to fight them down. Potential fields is a technique originating from the area of robotics where it is used in controlling the navigation of robots in dynamic environments. Although attempts have been made to transfer the technology to the gaming sector, assumed problems with efficiency and high costs for implementation have made the industry reluctant to adopt it. We present a Multi-agent Potential Field based bot architecture that is evaluated in a real time strategy game setting and compare it, both in terms of performance, and in terms of softer attributes such as configurability with other state-of-the-art solutions. Although our solution did not reach the performance standards of traditional RTS bots in the test, we see great unexploited benefits in using multi-agent potential field based solutions in RTS games.

  • 11. Shaker, Noor
    et al.
    Togelius, Julian
    Yannakakis, Georgios
    Poovanna, Likith
    Blekinge Institute of Technology, School of Computing.
    Ethiraj, Vinay
    Blekinge Institute of Technology, School of Computing.
    Johansson, Stefan
    Blekinge Institute of Technology, School of Computing.
    Gallagher, Marcus
    Reynolds, Robert
    Heether, Leonard
    Schumann,, Tom
    The turing test track of the 2012 Mario AI Championship: Entries and evaluation2013Conference paper (Refereed)
    Abstract [en]

    The Turing Test Track of the Mario AI Championship focused on developing human-like controllers for a clone of the popular game Super Mario Bros. Competitors participated by submitting AI agents that imitate human playing style. This paper presents the rules of the competition, the software used, the voting interface, the scoring procedure, the submitted controllers and the recent results of the competition for the year 2012. We also discuss what can be learnt from this competition in terms of believability in platform games. The discussion is supported by a statistical analysis of behavioural similarities and differences among the agents, and between agents and humans. The paper is co-authored by the organizers of the competition (the first three authors) and the competitors.

  • 12.
    Svensson, Johan
    et al.
    Blekinge Institute of Technology, School of Computing.
    Johansson, Stefan
    Blekinge Institute of Technology, School of Computing.
    Influence Map-based Controllers for Ms. PacMan and the Ghosts2012Conference paper (Refereed)
    Abstract [en]

    Ms. Pac-Man, one of the classic arcade games has recently gained attention in the field of game AI through the yearly competitions of various kinds held at e.g. CIG. We have implemented an Influence Map-based controller for Ms. Pac-Man as well as for the ghosts within the game. We show that it is able to handle a number of various situations through the interesting behaviors emerging through the interplay of the different maps. It is also significantly better than the previous implementations based on similar techniques, such as potential fields.

1 - 12 of 12
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  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • fi-FI
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