11,580 research outputs found
Is There a Link between Economic Outcomes and Genetic Evolution? Cross-Country Evidence from the Major Histocompatibility Complex
This research develops a theory and presents empirical evidence of a link between economic outcomes and genetic evolution. Important properties for successful analysis of such a link are found in the adaptive immune system and particularly in the major histocompatibility complex (MHC), a genetically encoded complex involved in the defence against infections. The theory incorporates properties of the MHC in a model of mutual dependence and exhibits a trade-off in which every agent who is better off having an immune response different from that of others is also part of the protecting belt of others in a population, in which mounting similar immune responses is optimal. The data are based on large numbers of blood samples from 63 different populations. The cross-country estimates show a robust negative association between economic and health outcomes and MHC diversity and between average offers in ultimatum and trust games and MHC diversity. The analyses suggest that societies incorporating externalities from mutual dependence are economically more successful, and that the incorporation of such externalities is evident at the gene level.Economics ;
Is there a link between economic outcomes and genetic evolution? Cross-country evidence from the major histocompatibility complex
This research develops a theory and presents empirical evidence of a link between economicoutcomes and genetic evolution. Important properties for successful analysis of such a link arefound in the adaptive immune system and particularly in the major histocompatibilitycomplex (MHC), a genetically encoded complex involved in the defence against infections.The theory incorporates properties of the MHC in a model of mutual dependence and exhibitsa trade-off in which every agent who is better off having an immune response different fromthat of others is also part of the protecting belt of others in a population, in which mountingsimilar immune responses is optimal. The data are based on large numbers of blood samplesfrom 63 different populations. The cross-country estimates show a robust negative associationbetween economic and health outcomes and MHC diversity and between average offers inultimatum and trust games and MHC diversity. The analyses suggest that societiesincorporating externalities from mutual dependence are economically more successful, andthat the incorporation of such externalities is evident at the gene level.education, training and the labour market;
Densifying the sparse cloud SimSaaS: The need of a synergy among agent-directed simulation, SimSaaS and HLA
Modelling & Simulation (M&S) is broadly used in real scenarios where making
physical modifications could be highly expensive. With the so-called Simulation
Software-as-a-Service (SimSaaS), researchers could take advantage of the huge
amount of resource that cloud computing provides. Even so, studying and
analysing a problem through simulation may need several simulation tools, hence
raising interoperability issues. Having this in mind, IEEE developed a standard
for interoperability among simulators named High Level Architecture (HLA).
Moreover, the multi-agent system approach has become recognised as a convenient
approach for modelling and simulating complex systems. Despite all the recent
works and acceptance of these technologies, there is still a great lack of work
regarding synergies among them. This paper shows by means of a literature
review this lack of work or, in other words, the sparse Cloud SimSaaS. The
literature review and the resulting taxonomy are the main contributions of this
paper, as they provide a research agenda illustrating future research
opportunities and trends
A State-of-the-art Integrated Transportation Simulation Platform
Nowadays, universities and companies have a huge need for simulation and
modelling methodologies. In the particular case of traffic and transportation,
making physical modifications to the real traffic networks could be highly
expensive, dependent on political decisions and could be highly disruptive to
the environment. However, while studying a specific domain or problem,
analysing a problem through simulation may not be trivial and may need several
simulation tools, hence raising interoperability issues. To overcome these
problems, we propose an agent-directed transportation simulation platform,
through the cloud, by means of services. We intend to use the IEEE standard HLA
(High Level Architecture) for simulators interoperability and agents for
controlling and coordination. Our motivations are to allow multiresolution
analysis of complex domains, to allow experts to collaborate on the analysis of
a common problem and to allow co-simulation and synergy of different
application domains. This paper will start by presenting some preliminary
background concepts to help better understand the scope of this work. After
that, the results of a literature review is shown. Finally, the general
architecture of a transportation simulation platform is proposed
Modeling economic systems as locally-constructive sequential games
Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing
Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning
Learning anticipation in Multi-Agent Reinforcement Learning (MARL) is a reasoning paradigm where agents anticipate the learning steps of other agents to improve cooperation among themselves. As MARL uses gradient-based optimization, learning anticipation requires using Higher-Order Gradients (HOG), with so-called HOG methods. Existing HOG methods are based on policy parameter anticipation, i.e., agents anticipate the changes in policy parameters of other agents. Currently, however, these existing HOG methods have only been applied to differentiable games or games with small state spaces. In this work, we demonstrate that in the case of non-differentiable games with large state spaces, existing HOG methods do not perform well and are inefficient due to their inherent limitations related to policy parameter anticipation and multiple sampling stages. To overcome these problems, we propose Off-Policy Action Anticipation (OffPA2), a novel framework that approaches learning anticipation through action anticipation, i.e., agents anticipate the changes in actions of other agents, via off-policy sampling. We theoretically analyze our proposed OffPA2 and employ it to develop multiple HOG methods that are applicable to non-differentiable games with large state spaces. We conduct a large set of experiments and illustrate that our proposed HOG methods outperform the existing ones regarding efficiency and performance
Fault-Tolerant Adaptive Parallel and Distributed Simulation
Discrete Event Simulation is a widely used technique that is used to model
and analyze complex systems in many fields of science and engineering. The
increasingly large size of simulation models poses a serious computational
challenge, since the time needed to run a simulation can be prohibitively
large. For this reason, Parallel and Distributes Simulation techniques have
been proposed to take advantage of multiple execution units which are found in
multicore processors, cluster of workstations or HPC systems. The current
generation of HPC systems includes hundreds of thousands of computing nodes and
a vast amount of ancillary components. Despite improvements in manufacturing
processes, failures of some components are frequent, and the situation will get
worse as larger systems are built. In this paper we describe FT-GAIA, a
software-based fault-tolerant extension of the GAIA/ART\`IS parallel simulation
middleware. FT-GAIA transparently replicates simulation entities and
distributes them on multiple execution nodes. This allows the simulation to
tolerate crash-failures of computing nodes; furthermore, FT-GAIA offers some
protection against byzantine failures since synchronization messages are
replicated as well, so that the receiving entity can identify and discard
corrupted messages. We provide an experimental evaluation of FT-GAIA on a
running prototype. Results show that a high degree of fault tolerance can be
achieved, at the cost of a moderate increase in the computational load of the
execution units.Comment: Proceedings of the IEEE/ACM International Symposium on Distributed
Simulation and Real Time Applications (DS-RT 2016
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
LUNES: Agent-based Simulation of P2P Systems (Extended Version)
We present LUNES, an agent-based Large Unstructured NEtwork Simulator, which
allows to simulate complex networks composed of a high number of nodes. LUNES
is modular, since it splits the three phases of network topology creation,
protocol simulation and performance evaluation. This permits to easily
integrate external software tools into the main software architecture. The
simulation of the interaction protocols among network nodes is performed via a
simulation middleware that supports both the sequential and the
parallel/distributed simulation approaches. In the latter case, a specific
mechanism for the communication overhead-reduction is used; this guarantees
high levels of performance and scalability. To demonstrate the efficiency of
LUNES, we test the simulator with gossip protocols executed on top of networks
(representing peer-to-peer overlays), generated with different topologies.
Results demonstrate the effectiveness of the proposed approach.Comment: Proceedings of the International Workshop on Modeling and Simulation
of Peer-to-Peer Architectures and Systems (MOSPAS 2011). As part of the 2011
International Conference on High Performance Computing and Simulation (HPCS
2011
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