04171 Abstracts Collection -- Logic Based Information Agents

From 18.04.04 to 23.04.04, the Dagstuhl Seminar 04171 ``Logic Based Information Agents\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Reasoning about norms under uncertainty in dynamic environments

The behaviour of norm-autonomous agents is determined by their goals and the norms that are explicitly represented inside their minds. Thus, they require mechanisms for acquiring and accepting norms, determining when norms are relevant to their case, and making decisions about norm compliance. Up un- til now the existing proposals on norm-autonomous agents assume that agents interact within a deterministic environment that is certainly perceived. In prac- tice, agents interact by means of sensors and actuators under uncertainty with non-deterministic and dynamic environments. Therefore, the existing propos- als are unsuitable or, even, useless to be applied when agents have a physical presence in some real-world environment. In response to this problem we have developed the n-BDI architecture. In this paper, we propose a multi -context graded BDI architecture (called n-BDI) that models norm-autonomous agents able to deal with uncertainty in dynamic environments. The n-BDI architecture has been experimentally evaluated and the results are shown in this paper.This paper was partially funded by the Spanish government under Grant CONSOLIDER-INGENIO 2010 CSD2007-00022 and the Valencian government under Project PROMETEOH/2013/019.Criado Pacheco, N.; Argente, E.; Noriega, P.; Botti Navarro, VJ. (2014). Reasoning about norms under uncertainty in dynamic environments. International Journal of Approximate Reasoning. 55(9):2049-2070. https://doi.org/10.1016/j.ijar.2014.02.004S2049207055

Reasoning about norms under uncertainty in dynamic environments

The behaviour of norm-autonomous agents is determined by their goals and the norms that are explicitly represented inside their minds. Thus, they require mechanisms for acquiring and accepting norms, determining when norms are relevant to their case, and making decisions about norm compliance. Up until now the existing proposals on norm-autonomous agents assume that agents interact within a deterministic environment that is certainly perceived. In practise, agents interact by means of sensors and actuators under uncertainty with non-deterministic and dynamic environments. Therefore, the existing proposals are unsuitable or, even, useless to be applied when agents have a physical presence in some real-world environment. In response to this problem we have developed the n-BDI architecture. In this paper, we propose a multi-context graded BDI architecture (called n-BDI) that models norm-autonomous agents able to deal with uncertainty in dynamic environments. The n-BDI architecture has been experimentally evaluated and the results are shown in this paper. © 2014 Elsevier Inc. All rights reserved

Exploring the resource recovery potentials of municipal solid waste: a review of solid wastes composting in developing countries

Population explosion, high urbanization and improved living standards have induced rapid changes in quantities and materiacompositions of solid waste generation globally. Until recently solid waste disposal in landfills and open dump sites waconsidered more economical and it is the most widely used methods in developing countries. Hence the potentials in the othealternative methods such as the resource recovery and recycling and their integration into waste management have been scarcelassessed. However, the ever growing challenges posed by the rapidly increasing quantities and compositions of solid wastes ideveloping countries led to the searching for alternative waste disposal methods. In this regard the paper presented an assessmenof the resource potentials of municipal solid waste materials arising from cities in developing countries as a strategy fosustainable solid waste management. Using published data on solid waste composition the paper has identified that there is higpotentials of composting in the solid waste stream from cities in developing countries. In conclusion, it recommended the recoverof organic waste material and papers for composting and the recycling of plastic, metals, textiles and others to explore their resource recovery potentials. This will largely reduce the ultimate quantities of solid waste for disposal and lower the operatincosts. This strategy will achieve sustainable waste management in developing countries. It is hoped that the paper has provided useful guide for wastes management policy decisions in developing countries

Highly Cited Publications of Selected Indian Institutes of Technology (IITs): A Bibliometric Study

The study highlights the highly cited publications published by selected five Indian Institutes of Technology (IITs) during the period 2010-2020. The IITs are the institutes of eminence and produced the quality scholarly output. They always occupy top positions in the ranking of institutions by different agencies. The data has been collected from the Essential Science Indiactor (ESI) which is a tool of Web of Science database. A total of 468 highly cited articles have been downloaded and analysed. The various parameters considered for the study are the year-wise distribution of articles, subject-wise distribution; the renowned journals published these articles, and top-cited articles. The findings revealed that IIT-M has a larger amount of immensely cited articles, and the chosen IITs have followed the collaborative model of more than four authors. Chemistry, Physics, and Engineering are the subjects in which the hugely cited articles have been published. The study would assist the researchers, academicians and funding agencies in providing a general overview of the highly cited articles produced by IITs and also in identifying the trend in research

Introduction to normative multiagent systems

This article introduces the research issues related to and definition of normative multiagent systems. It also describes the papers selected from NorMAS05 that are part of this double special issue and relates the papers to each other

The Current State of Normative Agent-Based Systems

Recent years have seen an increase in the application of ideas from the social sciences to computational systems. Nowhere has this been more pronounced than in the domain of multiagent systems. Because multiagent systems are composed of multiple individual agents interacting with each other many parallels can be drawn to human and animal societies. One of the main challenges currently faced in multiagent systems research is that of social control. In particular, how can open multiagent systems be configured and organized given their constantly changing structure? One leading solution is to employ the use of social norms. In human societies, social norms are essential to regulation, coordination, and cooperation. The current trend of thinking is that these same principles can be applied to agent societies, of which multiagent systems are one type. In this article, we provide an introduction to and present a holistic viewpoint of the state of normative computing (computational solutions that employ ideas based on social norms.) To accomplish this, we (1) introduce social norms and their application to agent-based systems; (2) identify and describe a normative process abstracted from the existing research; and (3) discuss future directions for research in normative multiagent computing. The intent of this paper is to introduce new researchers to the ideas that underlie normative computing and survey the existing state of the art, as well as provide direction for future research.Norms, Normative Agents, Agents, Agent-Based System, Agent-Based Simulation, Agent-Based Modeling

The complexity of the climate-economy nexus: agent-based modelling and policy evaluation

While the consensus on the urgency of climate actions has grown in the last decades, what is the pathway to be followed to translate proposal into actions is still argument of debates in the climate change economics literature. Most economists believe that carbon pricing is the main and the most efficient option to reduce GHGs emissions, however a growing number of works point out that this result is highly dependent on the type of model used, claiming the superiority of a policy mix when a more realistic representation of the economy is used. My research work deals with the study of different climate policies with a complex system science approach, in particular, using the Eurace macroeconomic agent-based model. This work has two main objectives: first, to test the common belief that the carbon tax policy is the main and powerful instrument we have to induce the desired climate transition; second, to study the policy mix problem within the Eurace model economy, in particular, a mix of a carbon tax and a feed-in tariff policy. I enriched the Eurace model with a new agent, the climate module, to account for the climate-economy feedback. The economy affects the climate through greenhouse gas emissions from fossil fuels use for the energy production while the climate affects the economy damaging physical capital, with damages dependent on the temperature anomaly. Moreover, I introduced heterogeneity in the capital good sector, in order to include energy intensity improvements as a factor of technological change. In order to establish a relation between real world and model quantities, I followed an initialization procedure based on imposing physical constraints on model's quantities. I have developed an extended multi-criteria analysis method to evaluate policies performance accounting for both multiple objectives and variability of the outcomes of computational experiments. To pursue the research objectives I performed a set of computational experiments with the Eurace model, in which I analyzed a carbon tax policy, a feed-in tariff policy, and a mix of the two policies. Results of computational experiments show that the carbon tax is not the best performing climate policy when analyzed with the Eurace model, both the feed-in tariff and the policy mix perform better. This result is independent from the presence of climate damages. In absence of climate damages the PM performs better than its components, however, climate damages reduce the positive effects of the interaction between the components leading to higher economic costs for the same emission reduction obtained. According to the extended multi-criteria analysis, in presence of climate damages, the feed-in tariff policy is almost always preferred to the policy mix