Artificial Intelligence has made remarkable strides, demonstrating remarkable capabilities in specific tasks, from game playing to image generation and recognition. Much of this success relies on probabilistic reasoning – quantifying uncertainty based on available data. AI models learn patterns and predict outcomes with associated confidence levels. This is akin to calculating the odds at a roulette table; the outcomes are unknown, but the probabilities are well-defined. Th

I. Introduction: A. The Evolving Landscape of Multi-Agent Systems Multi-Agent Systems (MAS) represent a significant area within...

The field of Machine Learning (ML) has witnessed remarkable progress over the past decades, largely propelled by the success of deep neural networks (DNNs). These models have achieved state-of-the-art performance across a wide spectrum of tasks, from image recognition and natural language processing to complex game playing and beyond. However, despite their triumphs, DNNs exhibit certain limitations that motivate the exploration of alternative computational paradigms. Concern

Time, often conceived as a fundamental, objective dimension of the physical universe ticking forward with metronomic regularity, reveals itself upon closer inspection to be a profoundly subjective and cognitively constructed aspect of human experience. While clocks measure duration with impersonal precision, our internal sense of time stretches and compresses, influenced by emotion, attention, memory, and perhaps most intriguingly, the very language we use to describe it. Hu

Intelligence, broadly defined as the capacity to learn from experience, adapt to novel situations , solve problems, and shape one's...

Artificial Intelligence is rapidly permeating diverse aspects of modern life, influencing sectors from healthcare and finance to entertainment and transportation. Its increasing sophistication promises transformative potential, automating tasks, augmenting human capabilities, and offering new modes of problem-solving. However, this rapid integration is accompanied by growing ethical scrutiny. Concerns regarding fairness, accountability, transparency, bias, and the broader soc

Swarm Intelligence (SI) represents a significant paradigm within artificial intelligence , drawing inspiration from the collective behaviors of natural systems to solve complex computational problems. However, the conventional classification of SI algorithms often groups them monolithically or based on superficial characteristics like the inspiring organism, obscuring crucial differences in their underlying operational mechanisms. This article addresses this limitation by pro

The advent of Large Language Models has marked a significant milestone in artificial intelligence, demonstrating remarkable capabilities...

Reinforcement Learning has achieved remarkable success in simulated environments, mastering complex games like Go, Dota 2, and Atari from scratch. However, translating this success to real-world applications like robotics, healthcare, finance, and autonomous driving faces a significant hurdle: sample inefficiency . Standard RL algorithms often require millions, or even billions, of interactions with the environment to learn effective policies. In the real world, collecting s

Artificial Intelligence has made breathtaking strides, mastering complex games, generating human-quality text and images, and identifying patterns in vast datasets . Much of this success relies on what psychologists call crystallized intelligence  – the ability to utilize learned knowledge, facts, and skills accumulated over time. AI excels here, leveraging massive training data to become incredibly knowledgeable within specific domains. However, the true frontier, the capab

The adage, "The mind that created the problem is rarely the one that is best suited to solve it,"  resonates deeply across many fields,...

The landscape of Artificial Intelligence has been dramatically reshaped by a seemingly simple principle: scaling. We've observed, with...

The Generative AI today is one of breathtaking scale. We conjure digital minds from petabytes of data, wielding computational power...

The world of artificial intelligence is abuzz with talk of increasingly sophisticated AI agents capable of performing complex tasks. A...

We live in a time buzzing with talk about Artificial Intelligence . It’s presented as a game-changer, a super-smart helper that can do...

AI strives to create systems capable of intelligent behavior, often drawing inspiration from the most powerful intelligent system known: the human brain and mind. One influential cognitive mode is Global Workspace Theory (GWT) , originally proposed by cognitive psychologist Bernard Baars. GWT offers a framework for understanding consciousness , attention, and information integration – concepts crucial for developing more flexible, robust, and perhaps even understandable AI s

The pursuit of truly intelligent systems has traditionally focused on algorithms and data, often neglecting the crucial role of the physical body and its interaction with the environment. However, the theory of Embodied Cognition suggests that intelligence is not solely a product of the brain but emerges from the dynamic interplay between the brain, body, and environment. This perspective has profound implications for Antetic AI , where the collective intelligence of a sw

While artificial intelligence has made remarkable strides in recent years the advancements often exist within a limited, simulated world. These AI systems , operating primarily on abstract data, frequently lack the real-world understanding, common sense reasoning , and adaptability that characterize human intelligence . This has led to a growing recognition of the need for grounded intelligence : AI systems that are firmly rooted in the physical world and can learn and reas

Large Language Models (LLMs) like GPT-series, and their burgeoning cohort represent a paradigm shift in artificial intelligence, demonstrating unprecedented abilities in natural language processing. They generate astonishingly coherent text, translate languages with impressive fluency, and even craft diverse creative content. Yet, beneath this dazzling performance lies a fundamental challenge that strikes at the very core of intelligence : the problem of embodiment . Embodim

In the pursuit of Artificial General Intelligence (AGI), the focus often lies on designing complex algorithms and building massive...