Eva Onaindia

Eva Onaindia
Universitat Politècnica de València | UPV · Department of Computer Systems and Computation

PhD Computing Science

About

180
Publications
32,051
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1,786
Citations
Citations since 2017
35 Research Items
882 Citations
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2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150

Publications

Publications (180)
Article
A declarative action model is a compact representation of the state transitions of dynamic systems that generalizes over world objects. The specification of declarative action models is often a complex hand-crafted task. In this paper we formulate declarative action models via state constraints, and present the learning of such models as a combinat...
Conference Paper
The aim of this work is to explain the observed behaviour of a hybrid system (HS). The explanation problem is cast as finding a trajectory of the HS that matches some observations. By using the formalism of hybrid automata (HA), we characterize the explanations as the language of a network of HA that comprises one automaton for the HS and another o...
Article
Full-text available
The way of understanding online higher education has greatly changed due to the worldwide pandemic situation. Teaching is undertaken remotely, and the faculty incorporate lecture audio recordings as part of the teaching material. This new online teaching–learning setting has largely impacted university classes. While online teaching technology that...
Conference Paper
Full-text available
This paper introduces the Temporal Inference Problem (TIP), a general formulation for a family of inference problems that reason about the past, present or future state of some observed agent. A TIP builds on the models of an actor and of an observer. Observations of the actor are gathered at arbitrary times and a TIP encodes hypothesis on unobserv...
Article
Open and shared manufacturing factories typically dispose of a limited number of industrial robots and/or other production resources that should be properly allocated to tasks in time for an effective and efficient system performance. In particular, we deal with the dynamic capacitated production planning problem with sequence independent setup cos...
Article
Given a partially observed plan execution, and a set of possible planning models (models that share the same state variables but different action schemata), model recognition is the task of identifying the model that explains the observation. The paper formalizes this task and introduces a novel method that estimates the probability of a STRIPS mod...
Article
Full-text available
Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek to analyze the representativeness of the open and collaborative plat...
Article
Full-text available
Monitoring wellbeing and stress is one of the problems covered by ambient intelligence, as stress is a significant cause of human illnesses directly affecting our emotional state. The primary aim was to propose a deliberation architecture for an ambient intelligence healthcare application. The architecture provides a plan for comforting stressed se...
Article
Full-text available
This paper presents FENOCOP, a game-theoretic approach for solving non-cooperative planning problems that involve a set of self-interested agents. Each agent wants to execute its own plan in a shared environment but the plans may be rendered infeasible by the appearance of potential conflicts; agents are willing to coordinate their plans in order t...
Preprint
Full-text available
Open and shared manufacturing factories typically dispose of a limited number of robots that should be properly allocated to tasks in time and space for an effective and efficient system performance. In particular, we deal with the dynamic capacitated production planning problem with sequence independent setup costs where quantities of products to...
Article
Full-text available
Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classica...
Article
Observation decoding aims at discovering the underlying state trajectory of an acting agent from a sequence of observations. This task is at the core of various recognition activities that exploit planning as resolution method but there is a general lack of formal approaches that reason about the partial information received by the observer or leve...
Chapter
The paper presents a classical planning compilation for learning STRIPS action models from partial observations of plan executions. The compilation is flexible to different amounts and types of input knowledge, from learning samples that comprise partially observed intermediate states of the plan execution to samples in which only the initial and f...
Article
Recently, social media has been considered the fastest medium for information broadcasting and sharing. Considering the wide range of applications such as viral marketing, political campaigns, social advertisement, and so on, influencing characteristics of users or tweets have attracted several researchers. It is observed from various studies that...
Article
Full-text available
Research on AI is more and more focusing towards explainable technology that accounts for the outcomes of programs and products. One important aspect in this direction is the ability to recognize the behaviour patterns of our application in order to make sensible and informed decisions. In this work, we aim to uncover the behaviour of a planning ag...
Article
Full-text available
Promoting a tourist destination requires uncovering travel patterns and destination choices, identifying the profile of visitors and analyzing attitudes and preferences of visitors for the city. To this end, tourism-related data are an invaluable asset to understand tourism behaviour, obtain statistical records and support decision-making for busin...
Article
Full-text available
The mainstream of EU policies is heading towards the conversion of the nowadays electricity consumer into the future electricity prosumer (producer and consumer) in markets in which the production of electricity will be more local, renewable and economically efficient. One key component of a local short-term and medium-term planning tool to enable...
Article
This paper presents FAMA, a novel approach for learning STRIPS action models from observations of plan executions that compiles the learning task into a classical planning task. Unlike all existing learning systems, FAMA is able to learn when the actions of the plan executions are partially or totally unobservable and information on intermediate st...
Preprint
Full-text available
Automated planning technology has developed significantly. Designing a planning model that allows an automated agent to be capable of reacting intelligently to unexpected events in a real execution environment yet remains a challenge. This article describes a domain-independent approach to allow the agent to be context-aware of its execution enviro...
Conference Paper
Full-text available
Automated planning technology has developed significantly. Designing a planning model that allows an automated agent to be capable of reacting intelligently to unexpected events in a real execution environment yet remains a challenge. This article describes a domain-independent approach to allow the agent to be context-aware of its execution enviro...
Preprint
Full-text available
Approaches to goal-directed behaviour including online planning and opportunistic planning tackle a change in the environment by generating alternative goals to avoid failures or seize opportunities. However, current approaches only address unanticipated changes related to objects or object types already defined in the planning task that is being s...
Preprint
Full-text available
This paper presents a novel approach for learning STRIPS action models from examples that compiles this inductive learning task into a classical planning task. Interestingly, the compilation approach is flexible to different amounts of available input knowledge; the learning examples can range from a set of plans (with their corresponding initial a...
Article
This paper presents a novel approach for learning strips action models from examples that compiles this inductive learning task into a classical planning task. Interestingly, the compilation approach is flexible to different amounts of available input knowledge; the learning examples can range from a set of plans (with their corresponding initial a...
Conference Paper
Full-text available
Despite the progress in online planning, goal driven autonomy , and opportunistic planning, agents still need to be fed by carefully engineered models that are fine tuned for particular applications. Approaches to goal-directed behaviour tackle a change in the environment by generating alternative goals to avoid failures or seize opportunities. How...
Article
Causality is a fundamental part of reasoning to model the physics of an application domain, to understand the behaviour of an agent or to identify the relationship between two entities. Causality occurs when an action is taken and may also occur when two happenings come undeniably together. The study of causal inference aims at uncovering causal de...
Conference Paper
Full-text available
Approaches to goal-directed behaviour including online planning and opportunistic planning tackle a change in the environment by generating alternative goals to avoid failures or seize opportunities. However, current approaches only address unanticipated changes related to objects or object types already defined in the planning task that is being s...
Article
Full-text available
When self-interested agents plan individually, interactions that prevent them from executing their actions as planned may arise. In these coordination problems, game-theoretic planning can be used to enhance the agents’ strategic behavior considering the interactions as part of the agents’ utility. In this work, we define a general-sum game in whic...
Article
The development of cooperative Multi-Agent Planning (MAP) solvers in a distributed context encompasses the design and implementation of decentralized algorithms that make use of multi-agent communication protocols. In this paper, we present FMAP, a platform aimed at developing distributed MAP solvers such as MAP-POP, FMAP and MH-FMAP, among others.
Article
Cooperative multi-agent planning (MAP) is a relatively recent research field that combines technologies, algorithms, and techniques developed by the Artificial Intelligence Planning and Multi-Agent Systems communities. While planning has been generally treated as a single-agent task, MAP generalizes this concept by considering multiple intelligent...
Article
Full-text available
Temporal landmarks have been proved to be a helpful mechanism to deal with temporal planning problems, specifically to improve planners performance and handle problems with deadline constraints. In this paper, we show the strength of using temporal landmarks to handle the state trajectory constraints of PDDL3.0. We analyze the formalism of TempLM,...
Article
Full-text available
Many tourist applications provide a personalized tourist agenda with the list of recommended activities to the user. These applications must undoubtedly deal with the constraints and preferences that define the user interests. Among these preferences, we can find those that define the travel style of the user, such as the rhythm of the trip, the nu...
Article
This paper presents a planning system that uses defeasible argumentation to reason about context information during the construction of a plan. The system is designed to operate in cooperative multi-agent environments where agents are endowed with planning and argumentation capabilities. Planning allows agents to contribute with actions to the cons...
Article
Most of the current top-performing planners are sequential planners that only handle total-order plans. Although this is a computationally efficient approach, the management of total-order plans restrict the choices of reasoning and thus the generation of flexible plans. In this paper, we present FLAP2, a forward-chaining planner that follows the p...
Chapter
Full-text available
This article provides an overview of different multiagent environments that require the application of planning techniques. The main techniques and approaches to multiagent planning (MAP) existing in the literature as well as the coordination mechanisms used by the agents are presented. The content of the article is organized around two types of mu...
Conference Paper
Full-text available
This paper describes e-Tourism2.0, a web-based recommendation and planning system for tourism activities that takes into account the preferences that define the travel style of the user. e-Tourism2.0 features a recommender system with access to various web services in order to obtain updated information about locations, monuments, opening hours, or...
Conference Paper
Full-text available
Many real-work smart environments make use of IoT to be provided with context-aware services. Additionally, these environments require making decisions based on predictions about future actions. This involves the use of goal-directed behaviour which may need reasoning about new goals. This paper is devoted to analyze when a new goal can be formulat...
Conference Paper
Full-text available
In this paper, we present a smart tourism system that plans a tourist agenda and keeps track of the plan execution. A Recommendation System returns the list of places that best fit the individual tastes of the tourist and a planner creates a personalized agenda or plan with indication of times and durations of visits. The key component of the syste...
Conference Paper
Full-text available
In this paper, we analyze the sentiments derived from the conversations that occur in social networks. Our goal is to identify the sentiments of the users in the social network through their conversations. We conduct a study to determine whether users of social networks (twitter in particular) tend to gather together according to the likeness of th...
Article
Full-text available
This paper presents TempLM, a novel approach for handling temporal planning problems with deadlines. The proposal revolves around the concept of temporal landmark, a proposition that must be necessarily true in all solution plans to achieve the problem goals within their deadlines. The temporal landmarks extracted from the problem form a landmarks...
Article
Full-text available
We present a novel reactive execution model for planning control applications which repairs plan failures at runtime. Our proposal is a domain-independent regression planning model which provides good-quality responses in a timely fashion. The use of a regressed model allows us to work exclusively with the sufficient and necessary information to de...
Conference Paper
Full-text available
Almost every planner needs good heuristics to be efficient. Heuristic planning has experienced an impressive progress over the last years thanks to the emergence of more and more powerful estimators. However, this progress has not been translated to multi-agent planning (MAP) due to the difficulty of applying classical heuristics in distributed env...
Research
Full-text available
This paper presents a novel multi-agent reactive execution model that keeps track of the execution of an agent to recover from incoming failures. It is a domain-independent execution model, which can be exploited in any planning control application, embedded into a more general multi-agent planning framework. The multi-agent reactive execution mode...
Article
Almost every planner needs good heuristics to be efficient. Heuristic planning has experienced an impressive progress over the last years thanks to the emergence of more and more powerful estimators. However, this progress has not been translated to multi-agent planning (MAP) due to the difficulty of applying classical heuristics in distributed env...
Article
Full-text available
When two or more self-interested agents put their plans to execution in the same environment, conflicts may arise as a consequence, for instance, of a common utilization of resources. In this case, an agent can postpone the execution of a particular action, if this punctually solves the conflict, or it can resort to execute a different plan if the...
Conference Paper
Full-text available
When two or more self-interested agents put their plans to execution in the same environment, conflicts may arise as a consequence, for instance, of a common uti-lization of resources. In this case, an agent can post-pone the execution of a particular action, if this punc-tually solves the conflict, or it can resort to execute a different plan if t...
Article
Full-text available
In this paper, we present FLAP, a partial-order planner that accurately applies the least-commitment principle that governs traditional partial-order planning. FLAP fully exploits the partial ordering among actions of a plan and hence it solves more problems than other similar approaches. The search engine of FLAP uses a combination of different st...
Conference Paper
Full-text available
This paper presents a novel multi-agent reactive execution model that keeps track of the execution of an agent to recover from incoming failures. It is a domain-independent execution model, which can be exploited in any planning control application, embedded into a more general multi-agent planning framework. The multi-agent reactive execution mode...
Article
Full-text available
This paper proposes FMAP (Forward Multi-Agent Planning), a fully-distributed multi-agent planning method that integrates planning and coordination. Although FMAP is specifically aimed at solving problems that require cooperation among agents, the flexibility of the domain-independent planning model allows FMAP to tackle multi-agent planning tasks o...
Article
Full-text available
In this paper we present a temporal planning approach for handling problems with deadlines. The model relies on the extraction of temporal landmarks from the problem and the construction of a landmarks graph as a skeleton of the solution plan. A temporal landmark is a proposition that must be achieved in a solution plan to satisfy the problem deadl...
Article
Full-text available
Multi-agent planning (MAP) approaches are typically oriented at solving loosely coupled problems, being ineffective to deal with more complex, strongly related problems. In most cases, agents work under complete information, building complete knowledge bases. The present article introduces a general-purpose MAP framework designed to tackle problems...
Conference Paper
Full-text available
In this paper we present a multi-agent reactive planning mechanism for recovering from plan failures with the help of multiple agents. Our contribution is twofold: a proposal of a dynamic execution architecture embedded into a more general multi-agent planning framework, and a mechanism based on state-transition systems that allows execution agents...
Article
Full-text available
This paper presents a general approach to automatically compile e-learning models to planning, allowing us to easily generate plans, in the form of learning designs, by using existing domain-independent planners. The idea is to compile, first, a course defined in a standard e-learning language into a planning domain, and, second, a file containing...
Conference Paper
Full-text available
This work addresses the generation of a personalized treatment plan from multiple clinical guidelines, for a patient with multiple diseases (comorbid patient), as a multi-agent cooperative planning process that provides support to collaborative medical decision-making. The proposal is based on a multi-agent planning architecture in which each agent...
Article
In this paper, we present samap, whose goal is to build a software tool to help different people visit different cities. This tool integrates modules that dynamically capture user models, determine lists of activities that can provide more utility to a user given the past experience of the system with similar users, and generates plans that can be...
Article
Full-text available
A system is context-aware if it can extract, interpret and use context information and adapt its functionality to the current context of use. Multi-agent planning generalizes the problem of planning in domains where several agents plan and act together, and share resources, activities, and goals. This contribution presents a practical extension of...
Conference Paper
Full-text available
In this paper we present FLAP, a forward-chaining planner which works with partial-order plans. Unlike similar planners like OPTIC, FLAP follows the least-commitment principle of the traditional partial-order planning algorithm without establishing additional ordering constraints among actions during the search. This leads to the generation of more...
Conference Paper
Full-text available
Multi-agent planning (MAP) approaches have been typically conceived for independent or loosely-coupled problems to enhance the benefits of distributed planning between autonomous agents as solving this type of problems require less coordination between the agents' sub-plans. However, when it comes to tightly-coupled agents' tasks, MAP has been rele...
Article
Full-text available
In this paper we tackle the sailing strategies problem, a stochastic shortest-path Markov decision process. The problem of solving large Markov decision processes accurately and quickly is challenging. Because the computational effort incurred is considerable, current research focuses on finding superior acceleration techniques. For instance, the c...
Conference Paper
Full-text available
One of the current limitations for large-scale use of planning technology in real world applications is the lack of software platforms to integrate the full spec-trum of planning-related technologies: sensing, plan-ning, executing, monitoring, re-planning and learning from past experiences. In this paper, we present PELEA, a domain-independent onli...
Conference Paper
Full-text available
This contribution presents a practical extension of a theoretical model for multi-agent planning based upon DeLP, an argumentation-based defeasible logic. Our framework, named DeLP-MAPOP, is implemented on a platform for open multi-agent systems and has been experimentally tested, among others, in applications of ambient intelligence in the field o...
Article
Full-text available
A key issue in group recommendation is how to combine the individual preferences of different users that form a group and elicit a profile that accurately reflects the tastes of all members in the group. Most Group Recommender Systems (GRSs) make use of some sort of method for aggregating the preference models of individual users to elicit a recomm...
Article
Full-text available
The problem of solving large Markov decision processes accurately and quickly is challenging. Since the computational effort incurred is considerable, current research focuses on finding superior acceleration techniques. For instance, the convergence properties of current solution methods depend, to a great extent, on the order of backup operations...