- I am a researcher in Artificial Intelligence, with a background in Mathematics and Theoretical Physics. I obtained a ... moreI am a researcher in Artificial Intelligence, with a background in Mathematics and Theoretical Physics. I obtained a master's degree in Mathematical Physics in 2008 at the Universiteit van Amsterdam under supervision of Robert Dijkgraaf. In May 2015 I obtained my PhD in Artificial Intelligence at the IIIA-CSIC in Barcelona, under supervision of Carles Sierra. Currently I am working with Dongmo Zhang at Western Sydney University.
My main interest is in Automated Negotiations where utility functions do not have an explicit expression, but instead are defined in terms of some hard, time-consuming problem that may involve Logic, Game Theory and Constraint Satisfaction. One typical example of such a domain is the game of Diplomacy, which I have been using as a test-bed for my research. Furthermore, I am especially interested in applying techniques from General Game Playing to the field of Automated Negotiations.
In May 2014 I won the second prize in the Automated Negotiating Agents Competition and in July 2015 I have won the first prize in the first Computer Diplomacy Challenge which was part of the ICGA Computer Olympiad 2015.edit
The advancement of technologies for autonomous vehicles (AVs) provides great potential for intelligent traffic control and management in the future. The deployment of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and... more
The advancement of technologies for autonomous vehicles (AVs) provides great potential for intelligent traffic control and management in the future. The deployment of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) communications enable traffic control on road segments, intersections or regional road networks with more options, either centralized or decentralized. However, choosing these options is not purely technical but a trade-off between autonomous decision-making and system optimization. One useful quantitative criterion for such a trade-off is the price of anarchy (PoA) of autonomous decision-making. This paper analyses the price of anarchy for road networks with traffic of autonomous vehicles. We model a traffic network as a routing game in which vehicles are selfish agents who choose routes to travel autonomously to minimize travel delays caused by road congestion. Unlike existing research in which the latency function of road conge...
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This book constitutes the revised post-conference proceedings of the 17th European Conference on Multi-Agent Systems, EUMAS 2020, and the 7th International Conference on Agreement Technologies, AT 2020, which were originally planned to be... more
This book constitutes the revised post-conference proceedings of the 17th European Conference on Multi-Agent Systems, EUMAS 2020, and the 7th International Conference on Agreement Technologies, AT 2020, which were originally planned to be held as a joint event in Thessaloniki, Greece, in April 2020. Due to COVID-19 pandemic the conference was postponed to September 2020 and finally became a fully virtual conference. The 38 full papers presented in this volume were carefully reviewed and selected from a total of 53 submissions. The papers report on both early and mature research and cover a wide range of topics in the field of autonomous agents and multi-agent systems
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Multiuser museum interactives are computer systems installed in museums or galleries that allow several visitors to interact together with digital representations of artefacts and information from the museum’s collection. WeCurate is such... more
Multiuser museum interactives are computer systems installed in museums or galleries that allow several visitors to interact together with digital representations of artefacts and information from the museum’s collection. WeCurate is such a system, that allows users to collaboratively create a virtual exhibition from a cultural image archive. It provides a synchronised image browser across multiple devices to enable a group of users to work together to curate a collection of images. WeCurate uses electronic institutions to coordinate and synchronise the interactions between individuals, and it relies on agreement technologies (such as argumentation and computational social choice) for collective decision making. This paper provides an overview of the WeCurate application, describes its underlying electronic institution, and presents a brief introduction to its collective decision making mechanism.
The notion of electronic institution draws inspiration from traditional institutions. Both can be seen as “coordination artefacts that serve as an interface between the internal decision making of individuals and their (collective)... more
The notion of electronic institution draws inspiration from traditional institutions. Both can be seen as “coordination artefacts that serve as an interface between the internal decision making of individuals and their (collective) goals”. However, electronic institutions, unlike the conventional ones, are intended to work on-line and may involve the participation of humans as well as software agents. The EI/EIDE framework that we present in this chapter includes the formal metamodel (EI) for electronic institutions (EI), and a particular development environment (EIDE) for implementing EI-based models. One models an electronic institution as a network of scenes where agents establish and discharge commitments, through “conversations” that are constrained by procedural and functional conventions. The EI metamodel includes the formal languages used to specify an institution and the data structure, operations and operational semantics that need to be supported by a technological environment to run it
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The Automated Negotiating Agents Competition (ANAC) is an annual competition that compares the state-of-the-art algorithms in the field of automated negotiation. Although in recent years ANAC has given more and more attention to more... more
The Automated Negotiating Agents Competition (ANAC) is an annual competition that compares the state-of-the-art algorithms in the field of automated negotiation. Although in recent years ANAC has given more and more attention to more complex scenarios, the linear and bilateral negotiation domains that were used for its first few editions are still widely used as the default benchmark in automated negotiations research. In this paper, however, we argue that these domains should no longer be used, because they are too simplistic. We demonstrate this with an extremely simple new negotiation strategy called MiCRO, which does not employ any form of opponent modeling or machine learning, but nevertheless outperforms the strongest participants of ANAC 2012, 2013, 2018 and 2019. Furthermore, we provide a theoretical analysis which explains why MiCRO performs so well in the ANAC domains. This analysis may help researchers to design more challenging negotiation domains in the future.
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There are a number of available tools that support teachers in the management of lesson plans on the web. However, none of them is task-centred and support any form of lesson plan’s execution over the web. PeerLearn is an application that... more
There are a number of available tools that support teachers in the management of lesson plans on the web. However, none of them is task-centred and support any form of lesson plan’s execution over the web. PeerLearn is an application that allows both the design and the execution of lesson plans, where lesson plans are designed with respect to a selected rubric. PeerLearn uses electronic institutions to coordinate interactions, ensuring the rules set by the lesson plan are followed, and it relies on a trust-based model to calculate automated marks. The automated marks provide tremendous support for teachers when their online classrooms have massive numbers of students. This chapter provides an overview of the PeerLearn application, describes its underlying electronic institution, and presents a brief introduction to its automated assessment technology.
We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action:NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order to... more
We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action:NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order to test the algorithm we present a new variant of the Traveling Salesman Problem, in which there is not one, but many salesmen. The salesmen need to negotiate with each other in order to minimize the distances they have to cover. Finally we present the results of some tests we did with a simple implementation of the algorithm for
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In this chapter we introduce the PeerLearn methodology and its associated tools. We base the design of pedagogical workflows for students on the definition of rubrics (using PeerAssess) as the starting element that drives the creation of... more
In this chapter we introduce the PeerLearn methodology and its associated tools. We base the design of pedagogical workflows for students on the definition of rubrics (using PeerAssess) as the starting element that drives the creation of lesson plans (using LessonEditor). These plans run over our web platform (Peer-Flow). Students can evaluate one another following given rubrics and teachers can accept (or not) marks produced by a collaborative assessment tool (COMAS). Experimental results show that PeerLearn provide students with a highly satisfying new pedagogical experience and increased learning outcomes. Source URL: https://www.iiia.csic.es/en/node/54265 Links [1] https://www.iiia.csic.es/en/staff/ismel-brito [2] https://www.iiia.csic.es/en/staff/patricia-gutierrez [3] https://www.iiia.csic.es/en/bibliography?f[author]=108 [4] https://www.iiia.csic.es/en/staff/dave-de-jonge [5] https://www.iiia.csic.es/en/staff/lissette-lemus [6] https://www.iiia.csic.es/en/staff/nardine-osman ...
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This book and most of the research reported here came out of the European FP7 project PRAISE (EU FP7 number 388770), funded by the European Commission under program FP7-ICT-2011-8.
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Abstract. We introduce the new concept of community browsing: a group of people browsing the web together and simultaneously. Community browsing is part of the broader notion of shared experience, where individuals share the experience of... more
Abstract. We introduce the new concept of community browsing: a group of people browsing the web together and simultaneously. Community browsing is part of the broader notion of shared experience, where individuals share the experience of an event. We have developed a prototype of a mobile application that enables community browsing, and involves new technologies such as a peer-topeer Electronic Institution and bipolar preference aggregation.
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Abstract. WeCurate is a shared image browser for collaboratively curating a virtual exhibition from a cultural image archive. This paper is concerned with the evaluation and iteration of a prototype UI (User Interface) design to enable... more
Abstract. WeCurate is a shared image browser for collaboratively curating a virtual exhibition from a cultural image archive. This paper is concerned with the evaluation and iteration of a prototype UI (User Interface) design to enable this community image browsing. In WeCurate, several remote users work together with autonomic agents to browse the archive and to select, through negotiation and voting, a set of images which are of the greatest interest to the group. The UI allows users to synchronize viewing media, assists navigating the ...
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We investigate a problem that lies at the intersection of three research areas, namely Automated Negotiation, Vehicle Routing, and Multi-Objective Optimization. Specifically, we investigate the scenario that multiple competing logistics... more
We investigate a problem that lies at the intersection of three research areas, namely Automated Negotiation, Vehicle Routing, and Multi-Objective Optimization. Specifically, we investigate the scenario that multiple competing logistics companies aim to cooperate by delivering truck loads for one another, in order to improve efficiency and reduce the distance they drive. In order to do so, these companies need to find ways to exchange their truck loads such that each of them individually benefits. We present a new heuristic algorithm that, given one set of orders to deliver for each company, tries to find the set of all order-exchanges that are Pareto-optimal and individually rational. Furthermore, we present experiments based on real-world test data from two major logistics companies, which show that our algorithm is able to find hundreds of solutions in a matter of minutes.
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When studying extensive-form games it is commonly assumed that players make their decisions individually. One usually does not allow the possibility for the players to negotiate their respective strategies and formally commit themselves... more
When studying extensive-form games it is commonly assumed that players make their decisions individually. One usually does not allow the possibility for the players to negotiate their respective strategies and formally commit themselves to future moves. As a consequence, many non-zero-sum games have been shown to have equilibrium outcomes that are suboptimal and arguably counter-intuitive. For this reason we feel there is a need to explore a new line of research in which game-playing agents are allowed to negotiate binding agreements before they make their moves. We analyze what happens under such assumptions and define a new equilibrium solution concept to capture this. We show that this new solution concept indeed yields solutions that are more efficient and, in a sense, closer to what one would expect in the real world. Furthermore, we demonstrate that our ideas are not only theoretical in nature , but can also be implemented on bounded rational agents, with a number of experiments conducted with a new algorithm that combines techniques from Automated Negotiations, (Algorithmic) Game Theory, and General Game Playing. Our algorithm, which we call Monte Carlo Negotiation Search, is an adaptation of Monte Carlo Tree Search that equips the agent with the ability to negotiate. It is completely domain-independent in the sense that it is not tailored to any specific game. It can be applied to any non-zero-sum game, provided that its rules are described in Game Description Language. We show with several experiments that it strongly outperforms non-negotiating players, and that it closely approximates the theoretically optimal outcomes, as defined by our new solution concept.
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Existing work on Automated Negotiations commonly assumes the ne-gotiators' utility functions have explicit closed-form expressions, and can be calculated quickly. In many real-world applications however, the calculation of utility can be... more
Existing work on Automated Negotiations commonly assumes the ne-gotiators' utility functions have explicit closed-form expressions, and can be calculated quickly. In many real-world applications however, the calculation of utility can be a complex, time-consuming problem and utility functions cannot always be expressed in terms of simple formulas. The game of Diplomacy forms an ideal test bed for research on Automated Negotiations in such domains where utility is hard to calculate. Unfortunately, developing a full Diplomacy player is a hard task, which requires more than just the implementation of a negotiation algorithm. The performance of such a player may highly depend on the underlying strategy rather than just its negotiation skills. Therefore, we introduce a new Diplomacy playing agent, called D-Brane, which has won the first international Computer Diplomacy Challenge. It is built up in a modular fashion, disconnecting its negotiation algorithm from its game-playing strategy, to allow future researchers to build their own negotiation algorithms on top of its strategic module. This will allow them to easily compare the performance of different negotiation algorithms. We show that D-Brane strongly outplays a number of previously developed Diplomacy players, even when it does not apply negotiations. Furthermore, we explain the negotiation algorithm applied by D-Brane, and present a number of additional tools, bundled together in the new BANDANA framework, that will make development of Diplomacy-playing agents easier.
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A General Game player is a computer program that can play games of which the rules are only known at run-time. These rules are usually given as a logic program. General Game players commonly apply a tree search over the state space, which... more
A General Game player is a computer program that can play games of which the rules are only known at run-time. These rules are usually given as a logic program. General Game players commonly apply a tree search over the state space, which is time consuming. In this paper we therefore present a new method that allows a player to detect that a future state satisfies some beneficial properties, without having to explicitly generate that state in the search tree. This may lead to faster algorithms and hence to better performance. Our method employs a search algorithm that searches backwards through formula space rather than state space.
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Current negotiation algorithms often assume that utility has an explicit representation as a function over the set of possible deals and therefore for any deal its utility value can be calculated quickly. We argue however, that a more... more
Current negotiation algorithms often assume that utility has an explicit representation as a function over the set of possible deals and therefore for any deal its utility value can be calculated quickly. We argue however, that a more realistic model of negotiations would be one in which the negotiator has certain knowledge about the domain and must reason with this knowledge in order to determine the value of a proposal , which is time-consuming. We propose to use Game Description Language to model such negotiation scenarios, because this may enable us to apply existing techniques from General Game Playing to implement negotiating agents for such domains.
ABSTRACT Package delivery companies compete with each other and have costumers spread over wide areas. We propose a negotiation algorithm that allows companies and individual postmen to negotiate over who delivers what package. This way,... more
ABSTRACT Package delivery companies compete with each other and have costumers spread over wide areas. We propose a negotiation algorithm that allows companies and individual postmen to negotiate over who delivers what package. This way, package delivery can be made more efficient, yielding a higher profit and/or lower costs for all parties. Our system does not force competing companies to cooperate, but proposes solutions that allow all parties to increase their individual profit.
ABSTRACT Every social network has its own fixed, but different, set of rules that apply to all users. This reflects the fact that in real life every community has different norms depending on the relationships between its members.... more
ABSTRACT Every social network has its own fixed, but different, set of rules that apply to all users. This reflects the fact that in real life every community has different norms depending on the relationships between its members. Unfortunately this has required people to create many different social networks that exist next to each other even though they have largely overlapping sets of members. In this paper we argue that Electronic Institutions (EI) solve this problem by allowing to create a generic social network in which users can set up their own sub-communities with their own particular norms and protocols. Electronic Institutions make it easy for users to specify these protocols and norms in a visual way, and adapt them when necessary. Furthermore we present a new framework on top of the existing EI architecture that allows humans to interact in any EI. It can generate a graphic user interface from the institution-specification without the requirement of any extra programming or design. However, it still allows designers to design a more sophisticated, domain specific GUI.
Abstract. When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Finding someone to help out can be a stressful waste of time. Despite an increasingly networked world, technology falls... more
Abstract. When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Finding someone to help out can be a stressful waste of time. Despite an increasingly networked world, technology falls short in supporting such daily irritations. u-Help provides a platform for building a community of helpful people and supports them in finding help for day-to-day tasks. It relies on a trio of techniques that allow a requester and volunteer to find one another easily, and build up a community around such ...
Abstract This paper introduces the notion of experiences, which help situate agents in their environment, providing a concrete link on how the continually evolving environment impacts the evolution of an agent's BDI model.... more
Abstract This paper introduces the notion of experiences, which help situate agents in their environment, providing a concrete link on how the continually evolving environment impacts the evolution of an agent's BDI model. Then, using the notion of shared experience as a primitive construct, we develop a novel formal model of shared intention which we believe more adequately describes and motivates social behaviour than traditional BDI logics that focus on modelling individual agents. Whilst many philosophers have strongly argued that ...
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We investigate a problem that lies at the intersection of three research areas, namely Automated Negotiation, Vehicle Routing, and Multi-Objective Optimization. Specifically, we investigate the scenario that multiple competing logistics... more
We investigate a problem that lies at the intersection of three research areas, namely Automated Negotiation, Vehicle Routing, and Multi-Objective Optimization. Specifically, we investigate the scenario that multiple competing logistics companies aim to cooperate by delivering truck loads for one another, in order to improve efficiency and reduce the distance they drive. In order to do so, these companies need to find ways to exchange their truck loads such that each of them individually benefits. We present a new heuristic algorithm that, given one set of orders to deliver for each company, tries to find the set of all order-exchanges that are Pareto-optimal and individually rational. Furthermore, we present experiments based on real-world test data from two major logistics companies, which show that our algorithm is able to find hundreds of solutions in a matter of minutes.
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In this paper we present a new algorithm for negotiations in non-zero-sum games. Although games have been studied extensively, most game playing algorithms have been developed under the assumption that players do not communicate. Many... more
In this paper we present a new algorithm for negotiations in non-zero-sum games. Although games have been studied extensively, most game playing algorithms have been developed under the assumption that players do not communicate. Many real-world problems, however, can be modeled as non-zero-sum games in which players may mutually benefit if they coordinate their actions, which requires negotiation. The field of Automated Negotiations is another important topic in AI, but in this field one usually assumes that utility functions have explicit expressions and can therefore be calculated easily. Traditional approaches do not apply to domains in which the utility values are instead determined by the rules of a complex game. In this paper we aim to bridge the gap between General Game Playing and Automated Negotiations. Our algorithm is an adaptation of Monte Carlo Tree Search that allows players to negotiate. It is completely domain-independent in the sense that it is not tailored to any specific game. It can be applied to any non-zero-sum game, provided that its rules are described in Game Description Language.
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Electronic institutions provide a computational analogue of human institutions to engineer open environments in which agents can interact in an autonomous way while complying with the norms of an institution. We survey the currently... more
Electronic institutions provide a computational analogue of human institutions to engineer open environments in which agents can interact in an autonomous way while complying with the norms of an institution. We survey the currently available infrastructures to engineer open environments as electronic institutions: (i) AMELI, the coordination infrastructure which is core to run EIs; and (ii) the conversion of the AMELI infrastructure to run over a peer to peer network. We also discuss the type of applications that both infrastructures target at.
We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action: NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order... more
We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action: NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order to test the algorithm we present a new variant of the Traveling Salesman Problem, in which there is not one, but many salesmen. The salesmen need to negotiate with each other in order to minimize the distances they have to cover. Finally we present the results of some tests we did with a simple implementation of the algorithm for this problem.
We introduce a new multiagent negotiation algorithm for large and complex domains, called NB3. It applies Branch & Bound to search for good offers to propose. To analyze its performance we present a new problem called the Negotiating... more
We introduce a new multiagent negotiation algorithm for large and complex domains, called NB3. It applies Branch & Bound to search for good offers to propose. To analyze its performance we present a new problem called the Negotiating Salesmen Problem. We have conducted some experiments with NB3 from which we conclude that it manages to decrease the traveling cost of the agents significantly, that it outperforms random search and that it scales well with the complexity of the problem.
We propose an application that allows users to request other users for help with every-day tasks. Users can pay each other for these tasks by issuing contracts in which the requester promises to return the favor in the future by... more
We propose an application that allows users to request other users for help with every-day tasks. Users can pay each other for these tasks by issuing contracts in which the requester promises to return the favor in the future by performing some task for the other. Such contracts can be seen as an alternative currency, coined by the users themselves. Trust is an essential aspect of this system, as the issuer of a contract may fail to fulfill its commitments. Therefore, the application comes with a social network where users can leave comments about other users. Furthermore, our application includes a market place where users can exchange service contracts between each other, and a negotiation
Recently, it has been proposed that Game Description Language (GDL) could be used to define negotiation domains. This would open up an entirely new, declarative, approach to Automated Negotiations in which a single algorithm could... more
Recently, it has been proposed that Game Description Language (GDL) could be used to define negotiation domains. This would open up an entirely new, declarative, approach to Automated Negotiations in which a single algorithm could negotiate over any domain, as long as that domain is expressible in GDL. However, until now, the feasibility of this approach has only been demonstrated on a few toy-world problems. Therefore, in this paper we show that GDL is a truly unifying language that can also be used to define more general and more complex negotiation domains. We demonstrate this by showing that some of the most commonly used test-beds in the Automated Negotiations literature, namely Genius and Colored Trails, can be described in GDL. More specifically, we formally prove that the set of possible agreements of any negotiation domain from Genius (either linear or non-linear) can be modeled as a set of strategies over a deterministic extensive-form game. Furthermore, we show that this game can be effectively described in GDL and we show experimentally that, given only this GDL description, we can explore the agreement space efficiently using entirely generic domain-independent algorithms. In addition, we show that the same holds for negotiation domains in the Colored Trails framework. This means that one could indeed implement a single negotiating agent that is capable of negotiating over a broad class of negotiation domains, including Genius and Colored Trails.