Multi-agent Programming Language Research Articles

Simulation of Ascorbic Acid Release from Alginate‐Whey Protein Concentrates Microspheres at the Simulated Gastrointestinal Condition Using Netlogo Platform

AbstractIn this article, our earlier researches were applied for ascorbic acid (AA) release study from Alginate‐Whey Protein Concentrate (AL‐WPC‐AA) microcapsule at the simulated gastrointestinal media. So, we created an agent‐based simulator using NetLogo platform to develop the virtual release tools. Diffusion equation is then fitted to the experimental release data, and finally diffusion coefficient and permeability funded for each condition. Results indicated that this agent‐based model can simulate the AA release process well, and there is a good R2 values (above 88.3%) between experimental and model release data. Conversely, results also show that the presence of the shear force and enzymes (pepsin and pancreatin) at the simulated gastrointestinal conditions significantly increase diffusion coefficients and release rate. Finally, this research suggested that we can easily use this agent‐based model for various nutrients and different situations.Practical ApplicationsIn this work, we developed an efficient agent‐based simulator for release study of the encapsulated AA using NetLogo platform. Our model was built in the NetLogo platform, which is a multiagent programming language and modeling environment with a good documentation, user‐friendly environment and visualization abilities. Our simulation model is accessible for nonexpert users, and it is possible to change or adjust parts of our agent‐based model to adapt the virtual release process to a specific real process. This model is the first version of a release simulator using the NetLogo platform. This article demonstrated that NetLogo model can simulate the AA release from AL‐WPC‐AA microcapsules well with the high correlation coefficient value. Our research also depicted that this simulation model can provide a strong tool for AA release prediction.

Programming multi-agent systems

AbstractWith the significant advances in the area of autonomous agents and multi-agent systems in the last decade, promising technologies for the development and engineering of multi-agent systems have emerged. The result is a variety of agent-oriented programming languages, development frameworks, execution platforms, and tools that facilitate building and engineering of multi-agent systems. This paper provides an overview of the multi-agent programming research field and explains the aim and characteristics of various multi-agent programming languages and development frameworks. This overview is complemented with a discussion on the current trends and challenges in this research community.

Agent-based modeling of the immune system: NetLogo, a promising framework.

Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

An Integrated Simulation of Tsunami Hazard and Human Evacuation in La Punta, Peru

The 2011 Great East Japan earthquake and tsunami was a magnitude 9.0 Mw event that destroyed most structural tsunami countermeasures. However, approximately 90% of the estimated population at risk from the tsunami survived due to a rapid evacuation to higher ground or inland. Thus, tsunami evacuation is the most effective measure to reduce casualties. In this paper, we applied a new developed evacuation model integrated with the numerical simulation of tsunami for casualty estimation. This tool is to support decisions in disaster management and disaster prevention education. The model was developed in NetLogo, a multi-agent programming language and modeling environment for simulating complex phenomena. Geographic Information Systems (GIS) datasets are used as spatial input information for road and shelter locations. The TUNAMI model of Tohoku University is used for the integration of tsunami numerical simulation results. In this paper, the study is performed in a tsunami threatened urban area of Callao, Peru, called La Punta. Results show the various contributions of the model to disaster management and scenario analysis. Among the contributions are the casualty estimation in a tsunami risk area and the analysis of the spatial distribution of vertical evacuation shelters.

Agent-based Simulation of the 2011 Great East Japan Earthquake/Tsunami Evacuation: An Integrated Model of Tsunami Inundation and Evacuation

The 2011 Great East Japan Earthquake/Tsunami was a magnitude 9.0 Mw event that destroyed most structural tsunami countermeasures. However, approximately 90% of the estimated population at risk from the tsunami survived due to rapid evacuation to higher ground or inland. In this paper, we introduce an evacuation model integrated with a numerical simulation of a tsunami and a casualty estimation evaluation. The model was developed in Netlogo, a multi-agent programming language and modeling environment for simulating complex phenomena. GIS data are used as spatial input information for road and shelter locations. Tsunami departure curves are used as the start time for agents deciding to evacuate in the model. Pedestrians and car drivers decide their own goals and search for a suitable route through algorithms that are also used in the video game and artificial intelligence fields. Bottleneck identification, shelter demand, and casualty estimation are some of the applications of the simulator. A case study of the model is presented for the village of Arahama in the Sendai plain area of Miyagi Prefecture in Japan. A stochastic simulation with 1,000 repetitions of evacuation resulted in a mean of 82.1% (SD=3.0%) of the population evacuated, including a total average of 498 agents evacuating to a multi-story shelter. The results agree with the reported outcome of 90% evacuation and 520 sheltered evacuees in the event. The proposed model shows the capability of exploring individual parameters and outcomes. The model allows observation of the behavior of individuals in the complex process of tsunami evacuation. This tool is important for the future evaluation of evacuation feasibility and shelter demand analysis.

Agent-based approach to model commuter behaviour's day-to-day dynamics under pre-trip information

This study reports on the tentative use of a multi-agent micro-simulation framework to address the issue of assessing commuter behaviour's day-to-day dynamics under pre-trip information. A Bayesian updating model is adopted to capture the reasoning mechanism by which commuters update their travel time perceptions from one day to the next in light of information and their previous experience. The population of commuters is represented as a community of autonomous agents, and travel demand results from the decision-making deliberation performed by each individual of the population as regards route and departure time. The reasoning mechanism of commuters is modelled by means of a Belief, Desire and Intention architecture, which has been a central theme in the multi-agent systems literature since the early 1990s. Each part of this architecture is specified by a multi-agent programming language named as AgentSpeak (L). A simple simulation scenario was devised using a combination of Jason (a multi-agent simulator) and Paramics (a traffic simulator). The simulation results show that the overall performance of the system is very likely affected by exogenous information and personal travel experiences; also, accurate information can greatly affect driver's switching activities and improve daily commuting conditions. Moreover, the combination of micro-simulation and agent-based modelling technique shows a great potential to represent more realistic and more complex driver's behaviour under intelligent transport system environment.

A Research on Multi Agent Modeling Language

Multi Agent System (MAS) as a new theory and approach for application development has been bought to attention, while its practical utilization is limited by the technical provision and methodology. The multi agent programming language is a foundation for developing multi agent applications and carrying out multi agent simulations. The current researches on multi agent modeling and programming language are focused on the semantics, Integrated Development Environment (IDE), agent framework and the underlying multi agent platform more or less. This paper will raise the questions in designing a MAS programming language and present a new multi agent modeling language named MA-UML which is modeling paradigms independent.

The multi-agent programming contest from 2005–2010

The Multi-Agent Programming Contest is an annual international event on programming multi-agent systems: Teams of agents participate in a simulated cooperative scenario. It started in 2005 and is organised in 2010 for the sixth time. The contest is an attempt to stimulate research in the area of multi-agent system development and programming by (i) identifying key problems in the field and (ii) collecting suitable benchmarks that can serve as milestones for testing multi-agent programming languages, platforms and tools. This article provides a short history of the contest since it started and reports in more detail on the cows and cowboys scenario implemented for the 2008, 2009 and 2010 contest editions. We briefly discuss the underlying technological background and conclude with a critical discussion of the experiences and lessons learned.

Implementing reactive BDI agents with user-given constraints and objectives

CASO is an agent-oriented programming language based on AgentSpeak(L), one of the most influential abstract languages based on the beliefs-desires-intentions (BDI) architecture. For many applications, it is more convenient to let the user provide in real time, a more elaborate specification consisting of constraints and preferences over possible goal states. Then, let the system discover a plan for the most desirable among the feasible goal states. CASO incorporates constraints and objectives into the symbolic approach of reactive BDI model which lead to better expressive capabilities as well as more efficient computation. Jason is a fully-fledged interpreter for a much improved version of AgentSpeak(L). In this work, we modify Jason to incorporate the operational semantics of CASO. CASO also uses ECLiPSe, an open source constraint solver, to apply constraint solving techniques. Our preliminary results show that CASO can be used as a powerful multi-agent programming language in solving problems in complex application domains.

Property-based Slicing for Agent Verification

Programming languages designed specifically for multi-agent systems represent a new programming paradigm that has gained popularity over recent years, with some multi-agent programming languages being used in increasingly sophisticated applications, often in critical areas. To support this, we have developed a set of tools to allow the use of model-checking techniques in the verification of systems directly implemented in one particular language called AgentSpeak. The success of model checking as a verification technique for large software systems is dependent partly on its use in combination with various state-space reduction techniques, an important example of which is property-based slicing. This article introduces an algorithm for property-based slicing of AgentSpeak multi-agent systems. The algorithm uses literal dependence graphs, as developed for slicing logic programs, and generates a program slice whose state space is stuttering-equivalent to that of the original program; the slicing criterion is a property in a logic with LTL operators and (shallow) BDI modalities. In addition to showing correctness and characterizing the complexity of the slicing algorithm, we apply it to an AgentSpeak program based on autonomous planetary exploration rovers, and we discuss how slicing reduces the model-checking state space. The experiment results show a significant reduction in the state space required for model checking that agent, thus indicating that this approach can have an important impact on the future practicality of agent verification.

Flexible Communication of Agents based on FIPA-ACL

Communication in multi-agent systems is an important subject of the current research. In this paper, the syntax and semantics of a multi-agent programming language, called ECCS, are defined. We focus specially on the communication of agents. The main contribution of this paper is a new and flexible way of communication of agents. We finally work out a well known protocol as an example.

A fully abstract model for the exchange of information in multi-agent systems

In this paper,11This paper is an extended version of [7]. we present a semantic theory for the exchange of information in multi-agent systems. We consider the multi-agent programming language agent communication programming language, which integrates the paradigms of concurrent constraint programming and communicating sequential processes (CSP). The constraint programming techniques are used to represent and process information, whereas the synchronous communication mechanism from CSP is generalised to enable the exchange of information. The semantics of the language, which is based on a generalisation of traditional failure semantics, is shown to be fully abstract with respect to observing of each terminating computation its final global store of information.

Translations of Vocabularies in Systems of Communicating Agents

AbstractWe develop a programming framework for systems of agents that interact with each other in a shared environment. We model the common environment as a mathematical structure and assign to each agent a part of this environment as its expertise. This expertise is given by a syntactical signature composed of a collection of relation and function symbols, which gives rise to a window on the environment. The agents observe and manipulate their individual windows and additionally exchange information about them along interconnecting communication channels. During such communication steps the agents may introduce new mental concepts to act as translations of concepts from foreign signatures that are referred to in the information received. Finally, the agents maintain a private belief base, which together with their window on the environment constitutes their mental state. This all results in an abstract programming language of communicating agents, which incorporates and generalizes traditional programming concepts from the field of concurrency theory. The syntax for the language is given, followed by a semantical description in terms of a transition system. This system enables the formal derivation of computations and gives rise to an operational semantics of the multi-agent programming language.

On the Formal Specification and Verification of Multi-Agent Systems

This article describes first steps towards the formal specification and verification of multi-agent systems, through the use of temporal belief logics. The article first describes Concurrent METATEM, a multi-agent programming language, and then develops a logic that may be used to reason about Concurrent METATEM systems. The utility of this logic for specifying and verifying Concurrent METATEM systems is demonstrated through a number of examples. The article concludes with a brief discussion on the wider implications of the work, and in particular on the use of similar logics for reasoning about multi-agent systems in general.