This very short article aims to bring together the available bibliography on
multi-level (or multi-layer, multi-perspective, multi-view, multi-scale,
multi-resolution) agent-based modeling so that it is accessible to interested
researchers.

One of the strength of Virtual Organisations is their ability to dynamically
and rapidly adapt in response to changing environmental conditions. Dynamic
adaptability has been studied in other system areas as well and system
management through policies has crystallized itself as a very prominent
solution in system and network administration. However, these areas are often
concerned with very low-level technical aspects.

During the execution of large scale construction projects performed by
Virtual Organizations (VO), relatively complex technical models have to be
exchanged between the VO members. For linking the trade and transfer of these
models, a so-called multi-model container format was developed. Considering the
different skills and tasks of the involved partners, it is not necessary for
them to know all the models in every technical detailing. Furthermore, the
model size can lead to a delay in communication.

This work deals with coupling Clinical Decision Support System (CDSS) with
Computerized Prescriber Order Entry (CPOE) and their dynamic plugging in the
medical Workflow Management System (WfMS). First, in this paper we argue some
existing CDSS representative of the state of the art in order to emphasize
their inability to deal with coupling with CPOE and medical WfMS.

A Multi-Agent System is a distributed system where the agents or nodes
perform complex functions that cannot be written down in analytic form.
Multi-Agent Systems are highly connected, and the information they contain is
mostly stored in the connections. When agents update their state, they take
into account the state of the other agents, and they have access to those
states via the connections. There is also external, user-generated input into
the Multi-Agent System. As so much information is stored in the connections,
agents are often memory-less.

A multiagent system may be thought of as an artificial society of autonomous
software agents and we can apply concepts borrowed from welfare economics and
social choice theory to assess the social welfare of such an agent society. In
this paper, we study an abstract negotiation framework where agents can agree
on multilateral deals to exchange bundles of indivisible resources. We then
analyse how these deals affect social welfare for different instances of the
basic framework and different interpretations of the concept of social welfare
itself.

Many current large-scale multiagent team implementations can be characterized
as following the belief-desire-intention (BDI) paradigm, with explicit
representation of team plans. Despite their promise, current BDI team
approaches lack tools for quantitative performance analysis under uncertainty.
Distributed partially observable Markov decision problems (POMDPs) are well
suited for such analysis, but the complexity of finding optimal policies in
such models is highly intractable.

This study presents a georeferenced agent-based model to analyze the climate
change impacts on the ski industry in Andorra and the effect of snowmaking as
future adaptation strategy. The present study is the first attempt to analyze
the ski industry in the Pyrenees region and will contribute to a better
understanding of the vulnerability of Andorran ski resorts and the suitability
of snowmaking as potential adaptation strategy to climate change.

Multiagent learning is a necessary yet challenging problem as multiagent
systems become more prevalent and environments become more dynamic. Much of the
groundbreaking work in this area draws on notable results from game theory, in
particular, the concept of Nash equilibria. Learners that directly learn an
equilibrium obviously rely on their existence. Learners that instead seek to
play optimally with respect to the other players also depend upon equilibria
since equilibria are fixed points for learning. From another perspective,
agents with limitations are real and common.

Social dynamics determined by voting in a stochastic environment is analyzed
for a society composed of two cohesive groups of similar size. Within the model
of random walks determined by voting, explicit formulas are derived for the
capital increments of the groups against the parameters of the environment and
"claim thresholds" of the groups. The "unanimous acceptance" and "unanimous
rejection" group rules are considered as the voting procedures. Claim
thresholds are evaluated that are most beneficial to the participants of the
groups and to the society as a whole.

To a large degree information and services for chemical e-Science have become
accessible - anytime, anywhere - but not necessarily useful. The Rule Responder
eScience middleware is about providing information consumers with rule-based
agents to transform existing information into relevant information of practical
consequences, hence providing control to the end-users to express in a
declarative rule-based way how to turn existing information into personally
relevant information and how to react or make automated decisions on top of it.

In this paper we study the strengths and limitations of collaborative teams
of simple agents. In particular, we discuss the efficient use of "ant robots"
for covering a connected region on the Z^{2} grid, whose area is unknown in
advance, and which expands at a given rate, where $n$ is the initial size of
the connected region.

We show that regardless of the algorithm used, and the robots' hardware and
software specifications, the minimal number of robots required in order for
such coverage to be possible is \Omega({\sqrt{n}}).

Since many of the currently available multi-agent frameworks are generally
mostly intended for research, it can be difficult to built multi-agent systems
using physical robots. In this report I describe a way to combine the
multi-agent framework Jason, an extended version of the agent-oriented
programming language AgentSpeak, with Lego robots to address this problem. By
extending parts of the Jason reasoning cycle I show how Lego robots are able to
complete tasks such as following lines on a floor and communicating to be able
to avoid obstacles with minimal amount of coding.

The eigenvalue spectrum of the adjacency matrix of a network is closely
related to the behavior of many dynamical processes run over the network. In
the field of robotics, this spectrum has important implications in many
problems that require some form of distributed coordination within a team of
robots. In this paper, we propose a continuous-time control scheme that
modifies the structure of a position-dependent network of mobile robots so that
it achieves a desired set of adjacency eigenvalues.

In this paper we study the problem of tracking an object moving randomly
through a network of wireless sensors. Our objective is to devise strategies
for scheduling the sensors to optimize the tradeoff between tracking
performance and energy consumption. We cast the scheduling problem as a
Partially Observable Markov Decision Process (POMDP), where the control actions
correspond to the set of sensors to activate at each time step. Using a
bottom-up approach, we consider different sensing, motion and cost models with
increasing levels of difficulty.

Comparative benefits provided by the basic social strategies including
collectivism and egoism are investigated within the framework of democratic
decision-making. In particular, we study the mechanism of growing "snowball" of
cooperation.

Multi-agent systems where the agents are developed by parties with competing
interests, and where there is no access to an agent's internal state, are often
classified as `open'. The member agents of such systems may inadvertently fail
to, or even deliberately choose not to, conform to the system specification.
Consequently, it is necessary to specify the normative relations that may exist
between the agents, such as permission, obligation, and institutional power.
The specification of open agent systems of this sort is largely seen as a
design-time activity.

This paper investigates the effectiveness of creative versus uncreative
leadership using EVOC, an agent-based model of cultural evolution. Each
iteration, each agent in the artificial society invents a new action, or
imitates a neighbor's action. Only the leader's actions can be imitated by all
other agents, referred to as followers. Two measures of creativity were used:
(1) invention-to-imitation ratio, iLeader, which measures how often an agent
invents, and (2) rate of conceptual change, cLeader, which measures how
creative an invention is.

The Internet has changed the way business is conducted in many ways. For
example, in the field of procurement, the possibility to directly interact with
a trading partner has given rise to new mechanisms in the supply chain
management. One such interactive dynamic procurement, which lets both buyer and
seller software agents bid by potential buyer agents instead of static
procurement by vendors. Dynamic procurement decision could provide the buying
and selling channel to buyer, to avoid occurring condition that seller could
not deliver on the contract promise.

We study the asymptotic properties of distributed consensus algorithms over
switching directed random networks. More specifically, we focus on consensus
algorithms over independent and identically distributed, directed random
graphs, where each agent can communicate with any other agent with some
exogenously specified probability. While different aspects of consensus
algorithms over random switching networks have been widely studied, a complete
characterization of the distribution of the asymptotic value for general
\textit{asymmetric} random consensus algorithms remains an open problem.

Current approaches to the engineering of space software such as satellite
control systems are based around the development of feedback controllers using
packages such as MatLab's Simulink toolbox. These provide powerful tools for
engineering real time systems that adapt to changes in the environment but are
limited when the controller itself needs to be adapted.

In this paper, we study the dynamics of a viral spreading process in random
geometric graphs (RGG). The spreading of the viral process we consider in this
paper is closely related with the eigenvalues of the adjacency matrix of the
graph. We deduce new explicit expressions for all the moments of the eigenvalue
distribution of the adjacency matrix as a function of the spatial density of
nodes and the radius of connection. We apply these expressions to study the
behavior of the viral infection in an RGG.

It is well-known that the eigenvalue spectrum of the Laplacian matrix of a
network contains valuable information about the network structure and the
behavior of many dynamical processes run on it. In this paper, we propose a
fully decentralized algorithm that iteratively modifies the structure of a
network of agents in order to control the moments of the Laplacian eigenvalue
spectrum.

This paper gives an overview of a proposed strategy for the "Cows and
Herders" scenario given in the Multi-Agent Programming Contest 2009. The
strategy is to be implemented using the Jason platform, based on the
agent-oriented programming language Agent-Speak. The paper describes the
agents, their goals and the strategies they should follow.

We use the notion of a promise to define local trust between agents
possessing autonomous decision-making. An agent is trustworthy if it is
expected that it will keep a promise. This definition satisfies most
commonplace meanings of trust. Reputation is then an estimation of this
expectation value that is passed on from agent to agent.

We are exploring the enhancement of models of agent behaviour with more
"human-like" decision making strategies than are presently available. Our
motivation is to developed with a view to as the decision analysis and support
for electric taxi company under the mission of energy saving and reduction of
CO2, in particular car-pool and car-sharing management policies. In order to
achieve the object of decision analysis for user, we provide a human-agents
interactive spatial behaviour to support user making decision real time.

Organizations of Restricted Generality (ORGs) raise important issues for
formalizing norms that require extensions and revisions of previous
foundational work. For example, extension and revision is required of the
fundamental assumption of the Event Calculus:

Time-varying properties hold at particular time-points if they have been
initiated by an action at some earlier time-point, and not terminated by
another action in the meantime.

The simulation of vehicular traffic as well as pedestrian dynamics meanwhile
both have a decades long history. The success of this conference series, PED
and others show that the interest in these topics is still strongly increasing.
This contribution deals with a combination of both systems: pedestrians
crossing a street. In a VISSIM simulation for varying demand jam sizes of
vehicles as well as pedestrians and the travel times of the pedestrians are
measured and compared.

Bargaining networks model the behavior of a set of players that need to reach
pairwise agreements for making profits. Nash bargaining solutions are special
outcomes of such games that are both stable and balanced. Kleinberg and Tardos
proved a sharp algorithmic characterization of such outcomes, but left open the
problem of how the actual bargaining process converges to them. A partial
answer was provided by Azar et al. who proposed a distributed algorithm for
constructing Nash bargaining solutions, but without polynomial bounds on its
convergence rate.

Coordination between organizations on strategic, tactical and operation
levels leads to more effective and efficient supply chains. Supply chain
management is increasing day by day in modern enterprises. The environment is
becoming competitive and many enterprises will find it difficult to survive if
they do not make their sourcing, production and distribution more efficient.
Multi-agent supply chain management has recognized as an effective methodology
for supply chain management.

Display advertising has traditionally been sold via guaranteed contracts -- a
guaranteed contract is a deal between a publisher and an advertiser to allocate
a certain number of impressions over a certain period, for a pre-specified
price per impression. However, as spot markets for display ads, such as the
RightMedia Exchange, have grown in prominence, the selection of advertisements
to show on a given page is increasingly being chosen based on price, using an
auction. As the number of participants in the exchange grows, the price of an
impressions becomes a signal of its value.

In this paper, we consider the consensus problem of dynamical multiple agents
that communicate via a directed moving neighborhood random network. Each agent
performs random walk on a weighted directed network. Agents interact with each
other through random unidirectional information flow when they coincide in the
underlying network at a given instant. For such a framework, we present
sufficient conditions for almost sure asymptotic consensus. Some existed
consensus schemes are shown to be reduced versions of the current model.