Abstract
The increasing penetration of distributed energy sources, mainly based on renewable generation, calls for an urgent emergence of novel advanced methods to deal with the associated problems. The consensus behind smart grids (SGs) as one of the most promising solutions for the massive integration of renewable energy sources in power systems has led to the development of several prototypes that aim at testing and validating SG methodologies. The urgent need to accommodate such resources require alternative solutions. This chapter presents a multi-agent based SG simulation platform connected to physical resources, so that realistic scenarios can be simulated. The SG simulator is also connected to the Multi-Agent Simulator of Competitive Electricity Markets, which provides a solid framework for the simulation of electricity markets. The cooperation between the two simulation platforms provides huge studying opportunities under different perspectives, resulting in an important contribution to the fields of transactive energy, electricity markets, and SGs. A case study is presented, showing the potentialities for interaction between players of the two ecosystems: a SG operator, which manages the internal resources of a SG, is able to participate in electricity market negotiations to trade the necessary amounts of power to fulfill the needs of SG consumers. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
This paper proposes the use of ontologies to enable information and knowledge exchange, to test different electricity market models and to allow players from different systems to interact in common market environments. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as the complex and dynamic electricity markets. The main drivers are the markets' restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. An ontology to represent the concepts related to the Nord Pool Elspot market is proposed. It is validated through a case study considering the simulation of Elspot market. Results show that heterogeneous agents are able to effectively participate in the simulation by using the proposed ontologies to support their communications with the Nord Pool market operator.

Abstract
Artificial intelligence is transforming the way chatbots are created and used. The recent boom of artificial intelligence development is creating a whole new generation of intelligent approaches that enable a more efficient and effective design of chatbots. On the other hand, the increasing need and interest from the industry in artificial intelligence based solutions, is guaranteeing the necessary investment and applicational know-how that is pushing such solutions to a new dimension. Some relevant examples are e-commerce, health or education, which is the main focus of this work. This paper studies and analyses the impact that artificial intelligence models and solutions is having on the design and development of chatbots, when compared to the previously used approaches. Some of the most relevant current and future challenges in this domain are highlighted, which include language learning, sentiment interpretation, integration with other services, or data security and privacy issues.

Abstract
Electricity markets are complex and dynamic environments with very particular characteristics. Ambitious goals, including those set by the European Union, foster the increased use of distributed generation, essentially based on renewable energy sources. This requires major changes in electricity markets and energy systems, namely through the adoption of the smart grid paradigm. The use of simulation tools and the study of different market mechanisms and the relationships between their stakeholders are essential. One of the main challenges in this area is developing decision support tools to address the problem as a whole. This work contributes to increasing interoperability between heterogeneous systems, namely agent-based, directed to the study of electricity markets, the operation of smart grid, and energy management. To this end, this work proposes the use of ontologies to ease the interaction between entities of different natures and the use of semantic web technologies to develop more intelligent and flexible tools. A multiagent systems society, composed of several heterogeneous multiagent systems, which interact using the proposed ontologies, is presented as a proof-of-concept. © 2021, Springer Nature Switzerland AG.

Abstract
Peer-to-Peer (P2P) energy trading (ET) is a paradigm of energy trading between consumers without intermediaries. This model of ET allows the commercialization of energy resources produced through renewable sources that do not need other local consumers. This energy trading between consumers is able to improve the local balance of energy generation and consumption. Currently, this paradigm is being evaluated to show the suitability of its application in today’s society, significantly increasing the number of projects in this area worldwide. This article reviews the main models of application of this paradigm in smart cities, presenting the main characteristics of these approaches. This paper proposes an architectural model for P2P energy trading that solves the main deficiencies detected. The designed system allows the simulation of P2P processes using a novel negotiation model. This energy trading system is based on a Multi-Agent System (MAS) using the Robot Operating System (ROS). The system allows representing using independent agents each one of the zones that intervene in the process of negotiation of the energy of a city, being already representing a consumer’s role or a producer’s role of energy. The system has been tested on a model in which each zone uses real data about the role it simulates over a period of two and a half years. The preliminary results show how the energy trading market allows a smart city to evolve towards a high degree of sustainability. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
This paper explores the concept of the Local Energy Market and, in particular, the need for Trust in the negotiations necessary for this type of market. A multi-agent system is implemented to simulate the Local Energy Market, and a Trust model is proposed to evaluate the proposals sent by the participants, based on forecasting mechanisms that try to predict the expected behavior of the participant. A case study is carried out with several participants who submit false negotiation proposals to assess the ability of the proposed Trust model to correctly evaluate these participants. The results obtained demonstrate that such an approach has the potential to meet the needs of the local market. © Springer Nature Switzerland AG 2020.