1,721,329 research outputs found
PyGenbot for IoT: A demonstration of how to generate any restricted stateless AIML FAQ-chatter bot from text files
No full textInternet of things applications (IoT) are required to interact with the user in the best natural possible way; the voice based conversation is the ultimate human-machine interaction in terms of easy to use and requirements from the user part, which also has the advantage for the user to interact hands free, non necessary watching a computer screen. Chatter bots are conversational agents that simulate, and capable to sustain, a conversation with a human. Technology do exists that allows to create a lexical knowledge base to be used by a restricted chatter bot, i.e. expert on a specific dominion. This work shows a methodology of restricted chatbot generation using Python program, called PyGenbot, that is capable to derive an AIML (Artificial Intelligence Markup Language) knowledge base starting from a simple textual data set, including: a FAQ, a keywords, a stopwords, a multiwords and a glossary file set. Any WOA attendee is welcome to supply arbitrary and simple formatted text files; then using PyGenbot, I will first edit the text input files needed to generate automatically the corresponding AIML knowledge base set that can be used with any standard AIML interpreter to implement the desired chatter bot, which can then be integrated into an IoT application
Digital forensics and investigations meet artificial intelligence
No full textIn the frame of Digital Forensic (DF) and Digital Investigations (DI), the “Evidence Analysis” phase has the aim to provide objective data, and to perform suitable elaboration of these data so as to help in the formation of possible hypotheses, which could later be presented as elements of proof in court. The aim of our research is to explore the applicability of Artificial Intelligence (AI) along with computational logic tools – and in particular the Answer Set Programming (ASP) approach — to the automation of evidence analysis. We will show how significant complex investigations, hardly solvable for human experts, can be expressed as optimization problems belonging in many cases to the P or NP complexity classes. All these problems can be expressed in ASP. As a proof of concept, in this paper we present the formalization of realistic investigative cases via simple ASP programs, and show how such a methodology can lead to the formulation of tangible investigative hypotheses. We also sketch a design for a feasible Decision Support System (DSS) especially meant for investigators, based on artificial intelligence tools
L’Atlante Linguistico ed Etnografico Informatizzato della Conca Aquilana (ALEICA): presentazione della versione definitiva
No full textPresentazione dell'ultima versione dell'ALEICA Atlante linguistico multimediale della conca aquilan
BlocksBot: Towards an Empathic Robot Offering Multi-modal Emotion Detection Based on a Distributed Hybrid System
No full textStudies show that people expectations on robots and their behavior are similar to those regarding living objects, and that users ascribe robots with human attributes, qualities, and capabilities even when the robot is not conceived for social interaction. Actually, the increasing availability of sensors able to capture situational data makes it possible to achieve adaptive systems able to dynamically take into account users' and context information with unprecedented precision, thus showing some degree of empathy and emotional intelligence. Modern robots can use their sensors, like cameras and microphones, not only for their more traditional goals, but also for classifying human emotional states in order to emulate an empathic behavior, and to put the users at ease and tempt them in continuing the interaction. They can offer a human-like communication occurring over different verbal and non-verbal communication channels. Anyhow, since multi-modal emotion detection is a complex technique requiring a proper combination of all the deriving data, handling it can be very demanding, and maybe impossible to achieve for many machines because of hardware limitations or simply for an unaffordable battery power consumption, with an ultimate effect on usability, which can degrade up to an unacceptable degree. In this paper we discuss how these problems have been faced within the framework of the BlocksBot project and how its Hybrid Distributed approach allows to overcome such limitations
An application of declarative languages in distributed architectures: Asp and dali microservices
Full text linkIn this paper we introduce an approach to the possible adoption of Answer Set Programming (ASP) for the definition of microservices, which are a successful abstraction for designing distributed applications as suites of independently deployable interacting components. Such ASP-based components might be employed in distributed architectures related to Cloud Computing or to the Internet of Things (IoT), where the ASP microservices might be usefully coordinated with intelligent logic-based agents. We develop a case study where we consider ASP microservices in synergy with agents defined in DALI, a well-known logic-based agent-oriented programming language developed by our research group.In this paper we introduce an approach to the possible adoption of Answer Set Programming (ASP) for the definition of microservices, which are a successful abstraction for designing distributed applications as suites of independently deployable interacting components. Such ASP-based components might be employed in distributed architectures related to Cloud Computing or to the Internet of Things (IoT), where the ASP microservices might be usefully coordinated with intelligent logic-based agents. We develop a case study where we consider ASP microservices in synergy with agents defined in DALI, a well-known logic-based agent-oriented programming language developed by our research group
A Multi-Agent-System framework for flooding events
Full text linkThis paper presents the potential capabilities offered by an integrated multi-agent system comprising logical agents and a neural network, specialized in monitoring flood events for civil protection purposes Here we describe the idea of a framework – at the moment only partially developed – consisting of a set of intelligent agents, which perform various tasks and communicate with each other to efficiently generate alerts during flood crisis events, collaborating with a neural network, derived from the PSP-Net model, which is dedicated to the inspection and analysis of satellite images
Constraint-Procedural Logic Generated Environments for Deep Q-learning Agent training and benchmarking
Full text linkWhile training and benchmarking neural networks, a large and precise set of data and an efficient test environment are parts of a successful process. A good data set is usually produced with high effort in terms of cost and human work to satisfy the constraints imposed by the expected results. In the first part of this paper we focus on the specification of the properties of the solutions needed to build a data set rather than using common primitives of imperative programming, exploring the possibility to procedurally generate data-sets using constraint programming in Prolog. In this phase geometric predicates describe a virtual environment according to inter-space requirements. The second part is focused to test the generated data set in a machine learning context by means of an AI gym and space search techniques. We developed a deep Q-learning model based neural network agent in Python able to address the NP search problem in the virtual space; the agent has the goal to explore the generated virtual environment to seek for a target, improving its performance through a reinforced learning process. © 2022 Copyright for this paper by its authors
Multi-agent system engineering for emphatic human-robot interaction
No full textHuman-robot interactions have to take into account the natural multi-modal bidirectional communication model that is common among humans. The model does not rely just on speech and verbal exchange, but it shall include emotional exchange through different channels: face muscles, body posture, voice modulation, skin responses, odors, etc. While some aspects are feasible yet far from being adopted by daily robotic interaction with humans, the other ones can exploit current level of technology so as to be included in common, although complex, human-robot communication use cases. In order to cope in synergic but efficient and modular way with the various emphatic communication aspects, we propose to employ intelligent agents and multi-agent system. Such multi-agent system comprises a controller sub-system aboard the robot, which is coordinated by logical agents that can incorporate perceptive modules which generates state predicates, reason about them, plan, and deliver emotionally intelligent action while interacting with human beings, emulating as much as possible human empathy
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