Abstract: This paper describes the design, implementation, visualizations, results and lessons learned of a novel real-world socio-technical research system for the purpose of rescheduling train drivers in
the event of disruptions. The research system is structured according to the Actor-Agent paradigm: here agents assist in rescheduling tasks of train drivers. Coordination between agents is based on a team formation process in which possible rescheduling alternatives can be evaluated, based on constraints and preferences of involved human train drivers and dispatchers. The research system is the result of cooperation on decentralised multi-agent crew rescheduling between Netherlands Railways (NS) and the D-CIS Lab. The implementation is realized using the Cougaar framework and includes actual timetable and rolling stock schedule data and driver duty data.
Abstract: This paper describes the design of a socio-technical research system for the purpose of rescheduling train drivers in the event of disruptions. The research system is structured according to the Actor-Agent paradigm: Here agents assist in rescheduling tasks of train drivers. Coordination between agents is based on a team formation process in which possible rescheduling alternatives can be evaluated, based on constraints and preferences of involved human train drivers and dispatchers. The research aim is to explore
the effectiveness of a decentralized, flexible actor-agent based approach to crew rescheduling. The
research system is realized using the Cougaar framework and includes actual rolling stock schedule data and driver duty data. The current reduced-scale version shows promising results for the full-scale version end 2008.
Abstract: We describe several principles for designing Actor-Agent Communities (AAC) as collectives of autonomous problem solving entities (software agents and human experts) that self-organize and collaborate at solving complex problems. One of the main distinctive aspects of the AAC is their ability to integrate in a meaningful way the expertise and reasoning of humans with different information processing algorithms performed by software agents, without requiring a unique and complete description of the problem and solution spaces.
Abstract: This research report discusses human group characteristics as a stepping stone to study human-agent team characteristics and dynamics. A human-agent team, or so called actor-agent team (AAT) is a group of humans and agents who interact in a coherent and coordinated way towards a common goal. The concept of AATs relates to actor-agent communities (AACs), as AACs are groups of humans and artificial systems (socio-technical information systems) that intimately work together to achieve a common goal (i.e. solve a problem) (Iacob et al., 2009).
AATs are envisioned to increase human performance in (among others) safety and security domains, emergency management, and traffic control. However, the concept of AATs brings many challenges. Besides the realisation of agents as teammembers, and the realisation of real-world AATs, the interaction between agents and humans is a challenge. If agents are to become (task performing) group members, team membership requires much from agents regarding human-agent interaction. How should agents be designed to become teammembers in an AAT? How can humans best interact with agents? When do trust an agent, or rely on it?
This document discusses human group characteristics to draw implications for AAT dynamics. This document is a follow-up of Gouman et al. (2008) in which stages of team development, group membership and cohesion, subgroups, norms, roles, status, and leadership were discussed. The current report first addresses communication and decision making, after which team performance and implications for AATs are discussed.
Abstract: The collaboration between humans (actors) and artificial entities (agents) can be a potential performance boost.
Agents, as complementary artificial intelligent entities, can alleviate actors from certain activities, while enlarging
the collective effectiveness. This paper describes our approach for experimentation with actors, agents and their
interaction. This approach is based on a principled combination of existing empirical research methods and is
illustrated by a small experiment which assesses the performance of a specific actor-agent team in comparison with
an actor-only team in an incident management context. The REsearch and Simulation toolKit (RESK) is
instrumental for controlled and repeatable experimentation. The indicative findings show that the approach is viable
and forms a basis for further data collection and comparative experiments. The approach supports applied actor-
agent research to show its (dis)advantages as compared to actor-only solutions.
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: 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: 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: The increasing complexity of our world demands new perspectives on the role of technology in human decision making. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and traffic management, where humans need to engage in close collaborations with artificial systems to observe and understand the situation and respond in a sensible way. The book Interactive Collaborative Information Systems addresses techniques that support humans in situations in which complex information handling is required and that facilitate distributed decision-making. The theme integrates research from information technology, artificial intelligence and human sciences to obtain a multidisciplinary foundation from which innovative actor-agent systems for critical environments can emerge. It emphasizes the importance of building actor-agent communities: close collaborations between human and artificial actors that highlight their complementary capabilities in situations where task distribution is flexible and adaptive. This book focuses on the employment of innovative agent technology, advanced machine learning techniques, and cognition-based interface technology for the use in collaborative decision support systems.
Abstract: The main goal of this thesis is to provide a first overview of the current architectures the most able to design a cognitive agent. The notion of cognitive agent is in line with the Actor-Agent Community (AAC) project of D-CIS Lab (second part of this thesis). This project aims to design a prototype of an artificial system with cognitive capabilities (the cognitive agent) capable to interact with humans within a team (the Actor-Agent Community).
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: 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: Crew rescheduling in response to disruptions is a difficult problem, due to the additional (social) constraints imposed on human workforce. In the real-world domain of train driver rescheduling in the Netherlands, an actor-agent based approach is taken to (a) support human dispatchers and (b) accommodate individual train drivers’ preferences. This paper outlines the task-exchange team-configuration process including the role of the
various rescheduling constraints. The rescheduling approach is designed for operation in a real world environment: to this end, a number of heuristics are discussed that are currently being examined to optimize the solution finding process with respect to
three dimensions: performance, quality and clarity. The heuristics have been implemented in a research system, supporting the full driver-agent population, working on real world data. This effort is an ongoing study on novel multi-agent approaches to crew
rescheduling, and is the result of cooperation between Netherlands Railways and D-CIS Lab.