相关论文: Synthetic emotions and consciousness: exploring ar…

AI is moving from domain-specific autonomy in closed, predictable settings to large-language-model-driven agents that plan and act in open, cross-organizational environments. As a result, the cybersecurity risk landscape is changing in…

This paper proposes a unified framework in which consciousness emerges as a cycle-consistent, affectively anchored inference process, recursively structured by the interaction of emotion and cognition. Drawing from information theory,…

In the Post-Turing era, artificial intelligence increasingly shapes social coordination and meaning formation rather than merely automating cognitive tasks. The central challenge is therefore not whether machines become conscious, but…

An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus,…

The more AI agents are deployed in scenarios with possibly unexpected situations, the more they need to be flexible, adaptive, and creative in achieving the goal we have given them. Thus, a certain level of freedom to choose the best path…

We introduce the notion of online reactive planning with sensing actions for systems with temporal logic constraints in partially observable and dynamic environments. With incomplete information on the dynamic environment, reactive…

The importance and pervasiveness of emotions in our lives makes affective computing a tremendously important and vibrant line of work. Systems for automatic emotion recognition (AER) and sentiment analysis can be facilitators of enormous…

Modern progress in artificial intelligence permits to realize algorithms of adaptation for critical events (in addition to ERP). A production emergence, an appearance of new competitive goods, a major change in financial state of partners,…

The recent rapid advancements in artificial intelligence research and deployment have sparked more discussion about the potential ramifications of socially- and emotionally-intelligent AI. The question is not if research can produce such…

Situationally-aware artificial agents operating with competence in natural environments face several challenges: spatial awareness, object affordance detection, dynamic changes and unpredictability. A critical challenge is the agent's…

Identifying and resolving conflicts of interests is a key challenge when designing autonomous agents. For example, such conflicts often occur when complex information systems interact persuasively with humans and are in the future likely to…

With the development of foundation model (FM), agentic AI systems are getting more attention, yet their inherent issues like hallucination and poor reasoning, coupled with the frequent ad-hoc nature of system design, lead to unreliable and…

Large language model agents suffer from fundamental architectural problems: entangled reasoning and execution, memory volatility, and uncontrolled action sequences. We introduce Structured Cognitive Loop (SCL), a modular architecture that…

While increasing research focuses on the emotional well-being of agile team members, a significant gap remains in emotion monitoring studies for Scrum Masters and meeting organizers, whose impact on team dynamics is crucial. This paper…

This work seeks to study the beneficial properties that an autonomous agent can obtain by implementing a cognitive architecture similar to the one of conscious beings. Along this document, a conscious model of autonomous agent based in a…

Background: Requirements changes (RCs) are inevitable in Software Engineering. Research shows that emotional intelligence (EI) should be used alongside agility and cognitive intelligence during RC handling. Objective: We wanted to study the…

This position paper discusses the benefits of longitudinal behavioural research with customised AI tools for exploring the opportunities and risks of synthetic relationships. Synthetic relationships are defined as "continuing associations…

Over the past decades, research in cognitive and affective neuroscience has emphasized that emotion is crucial for human intelligence and in fact inseparable from cognition. Concurrently, there has been growing interest in simulating and…

Although many AI applications of interest require specialized multi-modal models, relevant data to train such models is inherently scarce or inaccessible. Filling these gaps with human annotators is prohibitively expensive, error-prone, and…

Towards human-like dialogue systems, current emotional dialogue approaches jointly model emotion and semantics with a unified neural network. This strategy tends to generate safe responses due to the mutual restriction between emotion and…