Enrico Pontelli

New Mexico State University | NMSU · Department of Computer Science

The Cumulative constraint is a foundamental global constraint, which naturally arises in a variety of problems related to scheduling with limited resources. Since its introduction, numerous propagation algorithms have been proposed, offering different tradeoffs between computational complexity and filtering power. Such diversity allows the resoluti...

This paper provides a survey of the literature on the application of Multi-agent Systems (MAS) technology for Smartgrids. Smartgrids represent the next generation electric network, as communities are developing self-sufficient and environmentally friendly energy production. As a cyber-physical system, the development of the vision of Smartgrids req...

This volume contains the Technical Communications presented at the 39th International Conference on Logic Programming (ICLP 2023), held at Imperial College London, UK from July 9 to July 15, 2023. Technical Communications included here concern the Main Track, the Doctoral Consortium, the Application and Systems/Demo track, the Recently Published Re...

The Power Trading Agent Competition (Power TAC) simulates numerous economic multi-agent trading scenarios where brokers trade in multiple power markets. A successful broker makes sound predictions about future energy supplies, demands, and costs in these markets and bids intelligently to gain profit. The broker who maintains the most profitable por...

Earlier epistemic planning systems for multi-agent domains generate plans that contain various types of actions such as ontic, sensing, or announcement actions. However, none of these systems consider untruthful announcements, i.e., none can generate plans that contain a lying or a misleading announcement. In this paper, we present a novel epistemi...

This paper provides an overview of the use of Prolog and its derivatives to sustain research and development in the fields of bioinformatics and computational biology. A number of applications in this domain have been enabled by the declarative nature of Prolog and the combinatorial nature of the underlying problems. The paper provides a summary of...

The AllDifferent constraint is a fundamental tool in Constraint Programming. It naturally arises in many problems, from puzzles to scheduling and routing applications. Such popularity has prompted an extensive literature on filtering and propagation for this constraint. This paper investigates the use of General Processing Units (GPUs) to accelerat...

The Cumulative constraint is one of the most important global constraints, as it naturally arises in a variety of problems related to scheduling with limited resources. Devising fast propagation algorithms that run at every node of the search tree is critical to enable the resolution of a wide range of applications. Since its introduction, numerous...

The action language mA∗ employs the notion of update models in defining transitions between states. Given an action occurrence and a state, the update model of the action occurrence is automatically constructed from the given state and the observability of agents. A main criticism of this approach is that it cannot deal with situations when agents’...

This paper studies belief correction and state transition for ontic actions in a multi-agent epistemic framework. When a full observer agent observes the execution of an action, he will correct his (possibly wrong) initial belief about the precondition of the action as well as his belief about his own observability. The paper shows that correcting...

Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans , that is, solutions to planning problems, that transform a given state of the world to another state. The development of efficient and scalable answer set solvers has provided a significant boost to the development of ASP-based planning systems. This paper surve...

Multi-core and highly connected architectures have become ubiquitous, and this has brought renewed interest in language-based approaches to the exploitation of parallelism. Since its inception, logic programming has been recognized as a programming paradigm with great potential for automated exploitation of parallelism. The comprehensive survey of...

Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, i.e., solutions to planning problems, that transform a given state of the world to another state. The development of efficient and scalable answer set solvers has provided a significant boost to the development of ASP-based planning systems. This paper surveys t...

The resolution of combinatorial optimization problems, especially in the area concerned with the sequencing of tasks (i.e., referred to as sequencing problems), is an important challenge. This domain covers a wide breadth of applications, e.g., expressed as scheduling or routing problems. Such problems can often be optimally solved using Constraint...

Multi-core and highly-connected architectures have become ubiquitous, and this has brought renewed interest in language-based approaches to the exploitation of parallelism. Since its inception, logic programming has been recognized as a programming paradigm with great potential for automated exploitation of parallelism. The comprehensive survey of...

Developing autonomous agents that can reason about the perspective of their (human or artificial) peers is paramount to realistically model a variety of real-world domains. Being aware of the state of mind of others is a key aspect in different fields—e.g., legal reasoning, business negotiations, ethical AI and explainable AI. In particular, in the...

Computational Thinking (CT) captures the mental processes used to model and solve problems using a computational processes. While often connected to programming, CT is a core problem-solving skill, which has been advocated by educational researchers as a core skill, at par with reading and comprehension. A variety of learning environments have been...

In this paper, we develop a heuristic, progression based conformant planner, called CNF, which represents belief states by a special type of CNF formulae, called CNF CNF-state. We define a transition function φCNF for computing the successor belief state resulting from the execution of an action in a belief state and prove that it is sound and comp...

We present an explanation system for applications that leverage Answer Set Programming (ASP). Given a program P, an answer set A of P, and an atom a in the program P, our system generates all explanation graphs of a which help explain why a is true (or false) given the program P and the answer set A. We illustrate the functionality of the system us...

This paper explores the challenge of encountering incorrect beliefs in the context of reasoning about actions and changes using action languages with sensing actions. An incorrect belief occurs when some observations conflict with the agent’s own beliefs. A common approach to recover from this situation is to replace the initial beliefs with belief...

Visual programming languages (VPLs) were designed to assist children in introductory programming courses. Unfortunately, despite the positive results in teaching, VPLs are believed to be inaccessible for children with visual impairments and low vision due to the dependency of visual graphics as both input and output methods. To identify the barrier...

Designing agents that reason and act upon the world has always been one of the main objectives of the Artificial Intelligence community. While for planning in “simple” domains the agents can solely rely on facts about the world, in several contexts, e.g. , economy, security, justice and politics, the mere knowledge of the world could be insufficien...

Designing agents that reason and act upon the world has always been one of the main objectives of the Artificial Intelligence community. While for planning in "simple" domains the agents can solely rely on facts about the world, in several contexts, e.g., economy, security, justice and politics, the mere knowledge of the world could be insufficient...

This article presents the design of a tangible tool for teaching basic programming concepts to students with visual impairments and low vision. Meeting the preliminary requirements of this ongoing project (Tangible input, cost-efficient, and minimal maintenance), the paper describes the design of the hardware of this prototype with inexpensive mate...

The paper proposes a framework for capturing how an agent’s beliefs evolve over time in response to observations and for answering the question of whether statements made by a third party can be believed. The basic components of the framework are a formalism for reasoning about actions, changes, and observations and a formalism for default reasonin...

Multi-agent systems have been employed to model, simulate and explore a variety of real-world scenarios. It is becoming more and more important to investigate formalisms and tools that would allow us to exploit automated reasoning in these domains. An area that has received increasing attention is the use of multi-agent systems which allow an agent...

A comprehensive phylogeny of species, i.e., a tree of life, has potential uses in a variety of contexts, including research, education, and public policy. Yet, accessing the tree of life typically requires special knowledge, complex software, or long periods of training. The Phylotastic project aims make it as easy to get a phylogeny of species as...

When a composite web service—i.e., a composition of individual web services—is executed and fails, it is desirable to reuse as much as possible the results that have been obtained thus far. For example, a travel agent, after receiving an order to arrange for a trip from LA to NY from a customer, would typically identify the flights and the hotels,...

Motivated by the difficulty in presenting computational results, especially when the results are a collection of atoms in a logical language, to users, who are not proficient in computer programming and/or the logical representation of the results, we propose a system for automatic generation of natural language descriptions for applications target...

Motivated by the difficulty in presenting computational results, especially when the results are a collection of atoms in a logical language, to users, who are not proficient in computer programming and/or the logical representation of the results, we propose a system for automatic generation of natural language descriptions for applications target...

This paper proposes Multi-context System for Optimization Problems (MCS-OP) by introducing conditional costassignment bridge rules to Multi-context Systems (MCS). This novel feature facilitates the definition of a preorder among equilibria, based on the total incurred cost of applied bridge rules. As an application of MCS-OP, the paper describes ho...

Distributed Constraint Optimization Problems (DCOPs) have emerged as one of the prominent multi-agent architectures to govern the agents’ autonomous behavior in a cooperative multi-agent system (MAS) where several agents coordinate with each other to optimize a global cost function taking into account their local preferences. They represent a power...

(1) A comprehensive phylogeny of species, i.e., a tree of life, has potential uses in a variety of contexts in research and education. This potential is limited if accessing the tree of life requires special knowledge, complex software, or long periods of training. (2) The Phylotastic project aims to use web-services technologies to lower the barri...

Declarative languages offer unprecedented opportunities for the use of parallelism to speed up execution. A declarative language, being not procedural, removes the need to perform operations in a strict order and reduces the number of dependencies among operations, thus opening the doors for concurrent execution. The potential for transparent explo...

This chapter provides a broad overview of howlogic programming, and more specifically Answer Set Programming (ASP), can be used to model and solve some popular and challenging classes of problems in the general domain of bioinformatics. In particular, the chapter explores the use of ASP in Genomics studies, such as Haplotype inference and Phylogene...

The Distributed Constraint Optimization Problem (DCOP) is an elegant paradigm for modeling and solving multi-agent problems which are distributed in nature, and where agents cooperate to optimize a global objective within the confines of localized communication. Since solving DCOPs optimally is NP-hard, recent effort in the development of DCOP algo...

Evolutionary Biologists have long struggled with the challenge of developing analysis workflows in a flexible manner, thus facilitating the reuse of phylogenetic knowledge. An evolutionary biology workflow can be viewed as a plan which composes web services that can retrieve, manipulate, and produce phylogenetic trees. The Phylotastic project was l...

Evolutionary Biologists have long struggled with the challenge of developing analysis workflows in a flexible manner, thus facilitating the reuse of phylogenetic knowledge. An evolutionary biology workflow can be viewed as a plan which composes web services that can retrieve, manipulate, and produce phylogenetic trees. The Phylotastic project was l...

Tangible interaction enables physical manipulation of digital data, making it ideal to support visually impaired students. Visually impaired students are frequently integrated in mainstream courses, collaborating with sighted peers and instructors. This paper describes a tangible block localization and tracking method, using small inexpensive senso...

We report on how the declarative nature of Answer Set Programming allows one to model and solve some well-known and challenging classes of problems in the general domain of bioinformatics. We briefly survey the main results appeared in the areas of genomics, structure prediction, and systems biology.

The paper presents a model suitable to support effective team work and collaborative learning in a distributed context (e.g. in the context of distance education). The model is an extension of the Affinity Research Group model, which has been effectively used to form learning teams with students from diverse backgrounds. The model, referred to as t...

This paper presents two prototypical epistemic forward planners, called EFP and PG-EFP, for generating plans in multi-agent environments. These planners differ from recently developed epistemic planners in that they can deal with unlimited nested beliefs, common knowledge, and capable of generating plans with both knowledge and belief goals. EFP is...

Evolutionary Biologists have long struggled with the challenge of developing analysis workflows in a flexible manner, thus facilitating the reuse of phylogenetic knowledge. An evolutionary biology workflow can be viewed as a plan which composes web services that can retrieve, manipulate, and produce phylogenetic trees. The Phylotastic project was l...

Answer Set Programming (ASP) has become, in recent years, the paradigm of choice for the logic programming community and for a wide variety of application domains. Thanks to its declarative nature, ASP offers excellent opportunities for performance improvements through transparent exploitation of parallelism. This Chapter provides a survey on the m...

This paper presents an extension of the Multi-Context Systems (MCS) framework to allow the encoding of preferences at the level of the contexts. The work is motivated by the observation that a naive use of preference logics at a context level in an MCS can lead to undesirable outcomes, such as inconsistency of the MCS. To address this issue, the pa...

Discrete optimization is a central problem in artificial intelligence. The optimization of the aggregated cost of a network of cost functions arises in a variety of problems including Weighted Constraint Programs (WCSPs), Distributed Constraint Optimization (DCOP), as well as optimization in stochastic variants such as the tasks of finding the most...

The field of Distributed Constraint Optimization has gained momentum in recent years thanks to its ability to address various applications related to multi-agent cooperation. While techniques for solving Distributed Constraint Optimization Problems (DCOPs) are abundant and have matured substantially since the field’s inception, the number of DCOP r...

The AAAI-17 workshop program included 17 workshops covering a wide range of topics in AI. Workshops were held Sunday and Monday, February 4-5, 2017 at the Hilton San Francisco Union Square in San Francisco, California, USA. This report contains summaries of 12 of the workshops, and brief abstracts of the remaining 5.

This paper proposes a generic approach to planning in the presence of incomplete information. The approach builds on an abstract notion of a belief state representation, along with an associated set of basic operations. These operations facilitate the development of a sound and complete transition function, for reasoning about effects of actions in...

In recent years, there has been an explosion in the popularity of hackathons — creative, participant-driven meetings at which software developers gather for an intensive bout of programming, often organized in teams. Hackathons have tangible and intangible outcomes, such as code, excitement, learning, networking, and so on, whose relative merits ar...

The problem addressed in this paper is the challenge arising in enabling collaborative learning in the context distance education models. While research has made quantum leaps in the development of both effective collaborative pedagogical models as well as online learning environments, the research at the intersection of these two areas has been sc...

This poster highlights a sociocultural analysis of a multifaceted K12 outreach program at New Mexico State University, a Hispanic Serving Institution that has had success recruiting local young women into the computer science department and beyond into the computing workforce. YWiC began in 2006 and has become a rich, extensive outreach program, re...

The field of Distributed Constraint Optimization has gained momentum in recent years, thanks to its ability to address various applications related to multi-agent cooperation. Nevertheless, solving Distributed Constraint Optimization Problems (DCOPs) optimally is NP-hard. Therefore, in large-scale, complex applications, incomplete DCOP algorithms a...

The field of Distributed Constraint Optimization has gained momentum in recent years thanks to its ability to address various applications related to multi-agent cooperation. While techniques to solve Distributed Constraint Optimization Problems (DCOPs) are abundant and have matured substantially since the field inception, the number of DCOP realis...

The IEEE Education Society, the IEEE Computer Society, and the American Society for Engineering Education Educational Research and Methods Division (ASEE ERM) sponsored the 46th Frontiers in Education (FIE) Conference in Erie, PA, USA, held October 12–15, 2016. James Sluss, President of the Society, Russell Meier, President of the ASEE ECE Division...

The Workshop Program of the Association for the Advancement of Artificial Intelligence’s Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) was held at the beginning of the conference, February 12-13, 2016. Workshop participants met and discussed issues with a selected focus — providing an informal setting for active exchange among rese...

The Workshop Program of the Association for the Advancement of Artificial Intelligence’s Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) was held at the beginning of the conference, February 12-13, 2016. Workshop participants met and discussed issues with a selected focus — providing an informal setting for active exchange among rese...

In this paper, we assess the effectiveness of an extension of Alice, named AliCe-VilLagE, which allows two students to work on the same project, with synchronous communication mechanisms and shared view of the same virtual working environment. The virtual environment supports multi-modal interactions among students (e.g., video, instant messaging)....

The application of DCOP models to large problems faces two main limitations: (i) Modeling limitations, as each agent can handle only a single variable of the problem; and (ii) Resolution limitations, as current approaches do not exploit the local problem structure withineach agent. This paper proposes a novel Multi-Variable Agent (MVA) DCOP decompo...

General Purpose Graphical Processing Units (GPUs) are affordable multi-core platforms, providing access to large number of cores, but at the price of a complex architecture with non-trivial synchronization and communication costs. This paper presents the design and implementation of a conflict-driven ASP solver, that is capable of exploiting the pa...

General Purpose Graphical Processing Units (GPUs) are affordable multi-core platforms, providing access to large number of cores, but at the price of a complex architecture with non-trivial synchronization and communication costs. This paper presents the design and implementation of a conflict-driven ASP solver, that is capable of exploiting the pa...

In multi-agent domains (MADs), an agent's action may not just change the world and the agent's knowledge and beliefs about the world, but also may change other agents' knowledge and beliefs about the world and their knowledge and beliefs about other agents' knowledge and beliefs about the world. The goals of an agent in a multi-agent world may invo...

This paper presents an extension of the Multi-Context Systems (MCS) framework to allow preferences to be expressed at the context level. The work is motivated by the observation that a casual use of preference logics at a context level in MCS can lead to undesirable outcomes (e.g., inconsistency of the MCS). To address this issue, the paper introdu...

This paper proposes a generic approach to planning in the presence of incomplete information. The approach builds on an abstract notion of a belief state representation, along with an associated set of basic operations. These operations facilitate the development of a sound and complete transition function, for reasoning about effects of actions in...

DISSECT (DIScover SciEnce through Computational Thinking) is a project aimed at introducing students to computer science principles by establishing computational thinking (CT) as a problem-solving technique within middle school and high school Science, Technology, Engineering, and Mathematics (STEM) courses. While DISSECT has shown successful integ...

This paper analyzes the efforts of DISSECT (DIScover SciEnce through Computational Thinking) to introduce computer science theories into K-12 Curricula. This is accomplished by teaching computational thinking (CT) problem solving techniques in existing STEM+C courses in select middle and high school classrooms in Las Cruces, New Mexico, USA. Data c...