Abstract: This report presents an overview of the state-of-the-art methods and models for planning for teams of embodied agents. Due to the nature of the real world, this means we focus on multi-agent planning in stochastic, partially observable systems. In particular we focus on decentralized partially observable Markov decision processes (Dec-POMDPs), partially observable stochastic games (POSGs) and related models. Regarding such models, we review complexity results and recently proposed methods for finding (approximate) solutions.
Abstract: Future command teams will exists of human and artificial actors. This paper introduces
a taxonomy of collaboration types in human – agent teams. Using two classifying
dimensions, coordination type and collaboration type, eight different classes of human
– agent collaborations transpire. These classes might aid designers in pinpointing the
socio-technical design issues associated with these kinds of hybrid organizations.
Abstract: This deliverable explores basic characteristics of human groups and teams in order to derive implications for actor-agent teams (AAT’s). From a socio-psychological group dynamics perspective group developmental stages, membership, cohesion, subgroups, social status, roles, norms and leadership are defined and explained in order to enhance the understanding of the processes that are part of human group behavior. The document subsequently briefly explains what ‘actor-agent-team’ means, making the assumption that the factors that play a role in human-only teams also play a role in AAT’s and putting further implications to discussion.
Abstract: In recent years, a number of research projects have been conducted to investigate how software agents can support collaboration among human crisis workers and assist them in performing their tasks. By allowing agents to assume the role of an equal team member instead of merely a supporting role, we could fully exploit the capabilities of agents. For example, wecould allow fire robots to take the place of firefighters for efficient fire ground operations in circumstances where fire fighters find difficulty in their activities because of
explosions, toxicleakage, heat, thick smoke hazards, etc. To allow agents in a team to be
treated as equal to humans, agents should behave a little like humans; issues associated with communication and coordination among team members become relevant as well.
In this thesis, we present a system for actor/agent teaming in simulated incident and crisis scenarios. In this system, agents are team members themselves, equal in status to human team members. The purpose of the system is to determine effectiveness of actor/agent teams compared to actor-only teams. Its main components are: a simulator called
RISK, Machinetta's proxy-based coordination framework which supports an actor/agent
team with coordination and planning facilities, and a communication framework that allows actors to communicate in natural language to their agent team members. Actors and agents are connected to this system in order to collaborate in incident and crisis scenarios simulated by RISK. A pilot experiment has revealed important values that can be measured regarding team performance.
Abstract: The insertion of intelligent agents as active participants in an organization will
significantly alter team dynamics in general, and will transform standard command
teams into adaptive human – agent teams. In order to benefit from the adaptive
capabilities that this new type of organization promises, we need collaboration
schemes between human and artificial actors that harmonize with their respective
competences and demands. This paper explores various types of human – agent teams, with a focus on the issues
involved with designing dynamic task allocation and proper human – agent
collaboration. To this end, we introduce a taxonomy of human – agent team types and
elaborate on the issues and challenges involved with each type.
Abstract: The DECIS Lab conducts research on Actor-Agent Communities, especially in the
domain of crisis response and management. The ICIS research program among others
hosts the SEAT (Sustained Effectiveness of Actor Agents Teams) research project in
which the researchers Dr. Niek Wijngaards, Dr. Masja Kempen and Dr. Manuela Viezzer
focus on the effectiveness over time of humans, agents, and teams composed thereof, in
difficult circumstances. Within this research project, theories and models are developed
which need to be tested in crisis situations. Decided was that ultimately a scenario
simulation toolkit is needed and that my project would explore and formulate
requirements for the use of scenarios and specifications of scenario aspects.
This report describes the results of this project. The scenario specification approach is
outlined and the (atomic) actions are described and illustrated in some detail.
Furthermore, this report describes the whole progress of the project. The student also
gives his personal evaluation about the project and the relevance to his education.
This graduation has several topics in which the student’s tasks and contributions lay.
These are each handled in detail further in this report.
• The student has created the game world concept which was based on the results
from the SES project. This resulted in a RDF specification. Details of these
specifications are found in chapter two.
• The student created several scenarios for a select number of researchers. These
scenarios have the intent to validate the researchers’ research and provide them
with some meaningful results. The student also created those scenarios in Game
, which functions as a simulation of the simulator.
• For future use, the student also created guidelines for scenario creation. These
topics can be found in chapter three.
• The student created a requirements document for the development phase of the
scenario toolkit. These requirements can be found in chapter four.
• Most importantly, the student also participated in the development process of the
RISK simulator toolkit, which resulted in consistency in design and construction
and that the original game world concept only received some limited changes.
This resulted in the development of the current version of the toolkit. This topic is
handled in chapter five of this document.
Abstract: Decision making during crises takes place in (multi-agency) teams, in a bureaucratic political context. As a
result, the common notion that during crises decision making should be done in line with a Command & Control
structure is invalid. This paper shows that the best way for crisis decision making teams in a bureaucratic
political context is to follow an integrative negotiation approach as the shared mental model of decision making.
This conclusion is based on an analysis of crisis decision making by teams in a bureaucratic political context.
First of all this explains why in a bureaucratic political context the Command & Control adage does not hold.
Secondly, this paper motivates why crisis decision making in such context can be seen as a negotiation process.
Further analysis of the given context shows that an assertive and cooperative approach suits crisis decision
Abstract: Multi-agent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, etc. Learning approaches to multi-agent control, many of them based on reinforcement learning (RL), are investigated in complex domains such as teams of mobile robots. However, the application of decentralized RL to low-level control tasks is not as intensively studied. In this paper, we investigate centralized and decentralized RL, emphasizing the challenges and potential advantages of the latter. These are then illustrated on an example: learning to control a two-link rigid manipulator. Some open issues and future research directions in decentralized RL are outlined.
Abstract: Knowledge management systems (KMS) are designed to support and enhance the process of creating, storing, retrieving and transferring knowledge. In this contribution we investigate the use of such systems for the acquisition of knowledge in humanitarian disaster response teams. First, we present a framework describing how KMS should enhance group process gains and alleviate group process losses, and create an effective learning environment for successfully supporting the acquisition of knowledge. Second, we describe ongoing research on the acquisition of knowledge in the Belgian humanitarian response team (B-FAST, for Belgian First Aid and Support Team) that uses Microsoft Groove as knowledge management system before, during and after their missions. Initial findings are presented based on participant observation and interviews of the B-FAST team during a large humanitarian exercise, along with plans for future research.
Abstract: In actor-agent teams human and artificial entities interact and cooperate in order to enhance and augment their individual and joint cognitive ergonomic and problem solving capabilities. Also actor-agent communities can benefit from ‘ambient cognition’, a novel further reaching concept than ambient intelligence that hardly takes into account the resource limitations and capabilities changing over time of both humans and agents in collaborative settings. The Dutch Companion project aims at the
realization of an agent that takes advantage of the ambient cognition concerning actor-agent system dynamics such that natural emotion-sensitive interaction with an actor over a longer period of time can be sustained. We elaborate on our vision of
pursuing ambient cognition within actor-agent systems and present the plans and expected results of the Dutch Companion project.
Abstract: In actor-agent teams human and artiﬁcial entities interact and cooperate in order to enhance and augment their individual and joint cognitive ergonomic and problem solving capabilities. Also actor-agent communities can beneﬁt from ‘ambient cognition’, a novel further reaching concept than ambient intelligence that hardly takes into account the resource limitations and capabilities changing over time of both humans and agents in collaborative settings. The Dutch Companion project aims at the realization of an agent that takes advantage of the ambient cognition concerning actor-agent system dynamics such that natural social and emotion-sensitive interaction with an actor over a longer period of time can be sustained. We elaborate on our vision of pursuing ambient cognition within actor-agent systems and brieﬂy describe the goals of the Dutch Companion project.
Abstract: Engineering complex highly-interactive systems consisting of both human and artiﬁcial agents (actor-agent communities) requires insight in the use and role of concepts by individuals and in interaction between individuals (both human and artiﬁcial). In this philosophically-oriented paper, the distinction between concept kinds is found to depend on processing differences for these kinds, rather than content-based or structural differences. In addition, this leads to the characterization of a new concept kind: affordance concepts. Our next step is to a) experiment with acquisition of affordance concepts and b) investigate the role of affordances for strategic management of teams.
Abstract: Humans primarily assess situations and plan for actions by (implicit) scenario-based analysis. Decision making in crisis management situations in The Netherlands unfortunately does not explicitly feature scenario-based analysis; not within teams nor between teams. In this article we formulate conditions for successful application of scenario-based analysis, based on our experiences in crisis management and crisis management exercises. The conditions are formulated and briefly assessed in a number of cases. An important implication for information systems support is identified and future research is announced.
Abstract: This research report describes an experiment regarding assessing the effectiveness of actor-agent teams within the SEAT project in the CDM cluster in the ICIS research program. This document focuses on the background of actor-agent teaming, and on a methodology to assess the performance of an actor-agent team in comparison with an actor-only team. The experimental design is described together with the measurements and analysis. The results show that the experimental setup using the REsearch and Simulation toolKit(RESK) provides a repeatable construct. The results of the current performance comparison show no large decrement; but also not a large increment in performance. This is mostly due to the current (low) level ofagent complexity, where improvements are needed in communication capabilities and (more) team-oriented helpful behavior.
Abstract: This white paper contains the report of a first try-out experiment regarding assessing the effectiveness of actor-agent teams within the SEAT project. This document describes the background, experimental design and measurements and analysis of a pilot experiment conducted in July 2008 with an actor-only team.
Abstract: The main objective of this document is to bring together our assumptions, models, definitions and other findings regarding actor-agent teams, and effectiveness thereof. As such, this whitepaper by the SEAT project contains our findings on sustained effectiveness of actor-agent teams of the first half of ICIS research programme. The foundations of our research reported herein are formed by three main topics: actor-agent teams, effectiveness, and methodology. This document contains material to gain insight in the width and scope of actor-agent communities, and should be treated as a starting point for additional research and explorations. These demarcations are necessary to restrict the amount of information and effort to manageable proportions.
Abstract: Urban Search and Rescue is a growing area of robotic research. The RoboCup Federation has recognized this, and has created the new Virtual Robots competition to complement its existing physical robot and agent competitions. In order to successfully compete in this competition, teams need to field multi-robot solutions that cooperatively explore and map an environment while searching for victims. This paper presents the results of the first annual RoboCup Rescue Virtual competition. It provides details on the metrics used to judge the contestants as well as summaries of the algorithms used by the top four teams. This allows readers to compare and contrast these effective approaches. Furthermore, the simulation engine itself is examined and real-world validation results on the engine and algorithms are offered.
Abstract: Collaboration environments impose high demands on humans and
artificial systems. Especially during critical tasks team members, including
humans, artificial systems and other (sub-) teams, require support to guarantee
their continued effectiveness. Effectiveness of individuals and teams is an
important ingredient for organizational effectiveness, managerial decision
quality, as well as for maintaining organizational awareness. In this position
paper we introduce our conceptual view on realizing sustained team
effectiveness, in which both the measurement of effectiveness and team
management play an important role. A unified, interdisciplinary approach
facilitates measuring effectiveness in more complex organizations.
Abstract: Collaboration environments impose high demands on humans and artificial systems. Especially during critical tasks team members, including humans, artificial systems and other (sub-) teams, require support to guarantee their continued effectiveness. Effectiveness of individuals and teams is an important ingredient for organizational effectiveness, managerial decision quality, as well as for maintaining organizational awareness. In this position paper we introduce our conceptual view on realizing sustained team effectiveness, in which both the measurement of effectiveness and team management play an important role. A unified, interdisciplinary approach facilitates measuring effectiveness in more complex organizations.