“Open world” environments are those in which novel objects, agents, events, and more can appear and contradict previous understandings of the environment. This runs counter to the “closed world” assumption used in most AI research, where the ...

This paper introduces an approach to the integration of open-ended learning in modular robotics. We aim to provide these robots, equipped with morphological adaptability, with the capability to autonomously learn utility models specific to each ...

• Domain Knowledge for machine learning is encoded in many forms.
• Knowledge representation utilizes mathematical equations, probabilistic relations, logic rules, knowledge graphs, and large language models (LLMs).
• Prior knowledge ...

We review current and emerging knowledge-informed and brain-inspired cognitive systems for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or few-shot learning. Data-driven machine learning models have ...

Recent advancements in AI and deep learning have created a growing demand for artificial agents capable of performing tasks within increasingly complex environments. To address the challenges associated with continuous learning constraints and ...

Concepts are central to reasoning and intelligent behaviour. Scientific evidence shows that conceptual development is fundamental for the emergence of high-cognitive phenomena. Here, we model such phenomena in a brain-inspired ...

The paper considers the task-driven approach to artificial intelligence. It is shown that, on the one hand, it generalizes such approaches as the agent-based approach and general artificial intelligence, and, on the other hand, ...

Advancements in autonomy are leading to an increased need for machines capable of collaborative effort with humans to achieve team goals. One way of enhancing these human-autonomous system work arrangements leverages the concept of a ...

Cognitive modeling and neuromorphic computing are two promising avenues to achieve AGI. However, neither of them has achieved intelligent agents with human-like proficiency so far. One possibility is that the two fields have developed in isolation ...

Human behavior is conditioned by codes and norms that constrain action. Rules, “manners,” laws, and moral imperatives are examples of classes of constraints that govern human behavior. These systems of constraints are “messy:” individual ...

In robotics, perception is usually oriented at understanding what is happening in the external world, while few works pay attention to what is occurring in the robot’s body. In this work, we propose an artificial somatosensory system, ...

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• An artificial somatosensory system is proposed.
• Examples of Current and Energy ...

IoT applications with their resource-constrained sensor devices can benefit from adjusting their operations to the phenomena they sense and the environments they operate in, leading to the paradigm of self-adaptive, autonomous, or ...

• Exploration of requirements for containerized AI platforms to serve IoT.
• Case ...

Intelligent Virtual Agents (IVAs) can provide users with a friendly experience and have a wide range of applications in the era of artificial intelligence. However, most of existing IVAs are designed for personal computers. Design and ...

Alertness is an important part of attention in human development and behavior. This system allows us to have different behaviors depending on the stimuli and the environment around us. Within the area of cognitive architectures, ...

One of the objectives of Artificial General Intelligence is to propose programs to solve tasks similarly to the way human beings do. The associative memory plays an essential role in the daily behavior of human beings: If we have a ...

The Causal Cognitive Architecture 5, a brain inspired cognitive architecture, is presented. The navigation map which holds features, procedures, and linkages in its spatially mapped cells, is the basic data structure of the ...

Memory and learning are essential functions in human beings as they allow us to acquire and store in the brain representations of thoughts, experiences, and behaviors, which are required for problem-solving in our daily life and mainly ...

The Causal Cognitive Architecture 3 is a biologically inspired cognitive architecture based heavily on navigation maps—arrays holding spatial navigation information about the external environment but also coopted by the architecture for much of ...

Inspired by the human vision system and learning, we propose a novel cognitive architecture that understands the content of raw videos in terms of objects without using labels. The architecture achieves four objectives: (1) Decomposing ...

• The paper presents a cognitive architecture that decomposes a visual scene in terms of objects without using labels.

Building a human-like integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthermore, a computational model that enables an ...

Human beings can effortlessly perceive stimuli through their sensory systems to learn, understand, recognize and act on our environment or context. Over the years, efforts have been made to enable cybernetic entities to be close to ...