The KGP model of Agency for Decision Making in e-Negotiation

We investigate the suitabilility of the KGP (Knowledge, Goals, Plan) model of agency for autonomous decision making in dynamically changing environments. In particular, we illustrate how this model supports the decision making process of an agent at different levels, while the agents generates goals, plans for these goals, and selects actions to achieve the goals that it has planned for. We also exemplify the approach by illustrating how the model and a prototype implementation in the PROSOCS platform can be adopted to support e-negotiation, using a particular kind of internet auctions as a case study

CRAFTING THE MIND OF PROSOCS AGENTS

PROSOCS agents are software agents that are built according to the KGP model of agency. KGP is used as a model for the mind of the agent, so that the agent can act autonomously using a collection of logic theories, providing the mind's reasoning functionalities. The behavior of the agent is controlled by a cycle theory that specifies the agent's preferred patterns of operation. The implementation of the mind's generic functionality in PROSOCS is worked out in such a way so it can be instantiated by the platform for different agents across applications. In this context, the development of a concrete example illustrates how an agent developer might program the generic functionality of the mind for a simple application. 20 2-4 105 131 Cited By :1

An Agent Architecture for Concurrent Bilateral Negotiations

Abstract. We present an architecture that makes use of symbolic decision-making to support agents participating in concurrent bilateral negotiations. The architecture is a revised version of previous work with the KGP model [23, 12], which we specialise with knowledge about the agent’s self, the negotiation opponents and the environment. Our work combines the specification of domain-independent decision-making with a new protocol for concurrent negotiation that revisits the well-known alternating offers protocol [22]. We show how the decision-making can be specialised to represent the agent’s strategies, utilities and prefer-ences using a Prolog-like meta-program. The work prepares the ground for supporting decision-making in concurrent bilateral negotiations that is more lightweight than previous work and contributes towards a fully developed model of the architecture

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

Sustainable Nutrient Management in a Typical Uruguayan Dairy Farm through Nutrient Budget and Modelling

La producción lechera uruguaya es fundamental para el país y está bajo la lupa por los impactos ambientales que provoca. Los impactos son principalmente el resultado de prácticas de manejo ineficientes, que conducen al uso excesivo de nutrientes, principalmente nitrógeno y fósforo, ocasionando un flujo excedente al medio ambiente que afecta ríos, aguas subterráneas y suelo. En este contexto, esta tesis de maestría tuvo como objetivo generar nuevos conocimientos para informar al sector lechero uruguayo para lograr una producción más sostenible al comprender qué prácticas de manejo maximizan el uso eficiente de los nutrientes y reducen el daño ambiental. También tuvo como objetivo contribuir a la planificación estratégica del Gobierno uruguayo para lograr sistemas lecheros sustentables. La tesis implementó un enfoque multi metodológico para el estudio de caso de un establecimiento lechero típico uruguayo a través de la aplicación de Balances de Nutrientes y un Modelo Multiagentes llamado ¨Gestión de Nitrógeno y Fósforo¨ (NPM). Los resultados combinados de su aplicación demostraron que, junto con el uso de prácticas de manejo correctas, es posible ser más eficientes en el uso de nutrientes y, de esta manera, los sistemas de producción lechera pueden depender menos de los aportes externos de nutrientes. Los principales hallazgos indicaron que la fijación biológica de nitrógeno, las dietas pastoriles, la carga animal y la acumulación de fósforo en los suelos son variables de gestión clave que afectan la eficiencia de uso de los nutrientes y los impactos ambientales. Además, se llegó a la conclusión de que la presentación y el debate de resultados de la investigación en un enfoque de aprendizaje colectivo entre investigadores y productores mejora la comprensión de las prácticas respetuosas con el medio ambiente, así como las funciones esenciales como gestores sostenibles de recursos naturales finitos.Agencia Nacional de Investigación e Innovació

Sustainable Nutrient Management in a Typical Uruguayan Dairy Farm through Nutrient Budget and Modelling

La producción lechera uruguaya es fundamental para el país y está bajo la lupa por los impactos ambientales que provoca. Los impactos son principalmente el resultado de prácticas de manejo ineficientes, que conducen al uso excesivo de nutrientes, principalmente nitrógeno y fósforo, ocasionando un flujo excedente al medio ambiente que afecta ríos, aguas subterráneas y suelo. En este contexto, esta tesis de maestría tuvo como objetivo generar nuevos conocimientos para informar al sector lechero uruguayo para lograr una producción más sostenible al comprender qué prácticas de manejo maximizan el uso eficiente de los nutrientes y reducen el daño ambiental. También tuvo como objetivo contribuir a la planificación estratégica del Gobierno uruguayo para lograr sistemas lecheros sustentables. La tesis implementó un enfoque multi metodológico para el estudio de caso de un establecimiento lechero típico uruguayo a través de la aplicación de Balances de Nutrientes y un Modelo Multiagentes llamado ¨Gestión de Nitrógeno y Fósforo¨ (NPM). Los resultados combinados de su aplicación demostraron que, junto con el uso de prácticas de manejo correctas, es posible ser más eficientes en el uso de nutrientes y, de esta manera, los sistemas de producción lechera pueden depender menos de los aportes externos de nutrientes. Los principales hallazgos indicaron que la fijación biológica de nitrógeno, las dietas pastoriles, la carga animal y la acumulación de fósforo en los suelos son variables de gestión clave que afectan la eficiencia de uso de los nutrientes y los impactos ambientales. Además, se llegó a la conclusión de que la presentación y el debate de resultados de la investigación en un enfoque de aprendizaje colectivo entre investigadores y productores mejora la comprensión de las prácticas respetuosas con el medio ambiente, así como las funciones esenciales como gestores sostenibles de recursos naturales finitos.Agencia Nacional de Investigación e Innovació

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

The complexity of the intangible digital economy: an agent-based model

Since the last 30 years, the economy has been undergoing a massive digital transformation. Intangible digital assets, like software solutions, web services, and more recently deep learning algorithms, artificial intelligence and digital platforms, have been increasingly adopted thanks to the diffusion and advancements of information and communication technologies. Various observers argue that we could rapidly approach a technological singularity leading to explosive economic growth. This research work as a whole is aimed at investigating potential consequences on our economy deriving from digital technological progress. In particular, the contribution of the thesis is both empirical, theoretical and related to model design. On the empirical side, I present a cross-country empirical analysis assessing the correlation between the growth rate of both tangible and intangible investments and different measures of productivity growth. The analysis results are used to inform the first of the two frameworks of the agent-based macro-model Eurace that I employ to assess the long-term impact of digital investments on economy. In particular, in the first framework, a total factor augmenting approach has been used in order to model the digital technological progress because of the significant and positive correlation between total factor productivity and ICT capital investments, composed by a combination of both tangible and intangible investments which includes ICT technologies, software and database. In the second framework, I propose a different and innovative approach in which digital technological progress influences the elasticity of substitution between capital and labour. In this way, an increase of the elasticity of substitution can be seen as an increase in the tasks that machines can perform replacing human beings. In order to develop this approach, I substitute the Cobb-Douglas production function used in the first framework with a Leontief technology in which input factors are represented by organizational units. In turn, the contribution of each unit is given by a combination of capital and labour. The second framework results to be more realistic because it allows to distinguish between the various activities performed in the companies and the different education levels characterizing the workforce employed. Computational experiments show the emergence of technological unemployment in the long-run with a high pace of intangible digital investments. However, in the elasticity augmenting framework compensation mechanisms work more effectively leading to lower unemployment levels compared to the total factor augmenting one. Both frameworks are able to capture interesting features and empirical evidences characterizing our economic system