Stan Franklin

The University of Memphis | U of M · Institute for Intelligent Systems

Much of our everyday, embodied action comes in the form of smooth coping. Smooth coping is skillful action that has become habituated and ingrained, generally placing less stress on cognitive load than considered and deliberative thought and action. When performed with skill and expertise, walking, driving, skiing, musical performances, and short-o...

Across various fields it is argued that the self in part consists of an autobiographical self-narrative and that the self-narrative has an impact on agential behavior. Similarly, within action theory, it is claimed that the intentional structure of coherent long-term action is divided into a hierarchy of distal, proximal, and motor intentions. Howe...

A body schema is an agent's model of its own body that enables it to act on affordances in the environment. This article presents a body schema system for the LIDA cognitive architecture. LIDA is a conceptual and computational implementation of Global Workspace Theory, also integrating other theories from neuroscience and psychology. This article c...

LIDA is a systems-level, biologically-inspired cognitive architecture. More than a decade of research on LIDA has seen much conceptual work on its learning mechanisms, and resulted in a set of conceptual commitments that constrain those mechanisms; perhaps the most essential of these constraints is the Conscious Learning Hypothesis from Global Work...

Natural selection has imbued biological agents with motivations moving them to act for survival and reproduction, as well as to learn so as to support both. Artificial agents also require motivations to act in a goal-directed manner and to learn appropriately into various memories. Here we present a biologically inspired motivation system, based on...

In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the pattern theory, as originally presented, stands as a mere list of aspects that fails to explain how they are related in real...

Pages 22 - 28 is my paper. It describes how we can use an ultra-delayed quantum eraser experiment to figure out when and where the wavefunction collapses.

This paper initiates language in LIDA by using the Learning Intelligent Decision. 1For historical reasons, this word was previously "distribution". It has been recently changed to better capture important aspects of the model in its name. ¹ Agent's (LIDA) perceptual learning mechanism to suggest how an infant vervet, Chlorocebus pygerthrus, learns...

Computational cognitive models of spatial memory often neglect difficulties posed by the real world, such as sensory noise, uncertainty, and high spatial complexity. On the other hand, robotics is unconcerned with understanding biological cognition. Here, we describe a computational framework for robotic architectures aiming to function in realisti...

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these 'cognitive maps' are not well understood. We propose that the structure of the representations of navigati...

Methodological details. (PDF)

Over a decade in the making and described in some seventy-five published papers, the LIDA cognitive model is comprehensive, complex, and hard to "wrap one's head around". Here we offer, in tutorial fashion, a current, relatively complete and somewhat detailed, description of the conceptual LIDA model, with pointers to more complete accounts of indi...

The ability to represent and utilize spatial information relevant to their goals is vital for intelligent agents. Doing so in the real world presents significant challenges, which have so far mostly been addressed by robotics approaches neglecting cognitive plausibility; whereas existing cognitive models mostly implement spatial abilities in simpli...

Modern tools and methods of cognitive science, such as brain imaging or computational modeling, can provide new insights for age-old philosophical questions regarding the nature of temporal experience. This chapter aims to provide an overview of functional consciousness and time perception in brains and minds (Section 8.2), and to describe a comput...

Humans estimate their movements based on their knowledge of the dynamics of the environment, and on actual sensory data. Wolpert and colleagues have incorporated this understanding into a model that simulates this estimation using the Kalman filter [1]. Inspired by a recent study in neuroscience [2], we here introduce a new factor—memory of errors—...

Although most cognitive architectures, in general, and LIDA, in particular, are still in the early stages of development and still far from being adequate bases for implementations of human-like ethics, we think that they can contribute to the understanding, design, and implementation of constrained ethical systems for robots, and we hope that the...

We present a new model of sensorimotor learning in a systems-level cognitive model, LIDA. Sensorimotor learning helps an agent properly interact with its environment using past experiences. This new model stores and updates the rewards of pairs of data, motor commands and their contexts, using the concept of reinforcement learning; thus the agent i...

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We...

This paper presents a cognitive model for an action execution process—the sensory motor system (SMS)—as a new module of the system-level cognitive model for “Learning Intelligent Distribution Agent” (LIDA). Action execution refers to a situation in which a software agent or robot transforms a selected goal-directed action into low-level executable...

The representation paradigm used by a cognitive architecture helps to determine the kind of processes that it can perform more efficiently. Vector LIDA is a variation of the LIDA cognitive architecture that employs high-dimensional Modular Composite Representation (MCR) vectors as its main representation model and Integer Sparse Distributed Memory...

Daniel Kahneman (2011) posits two main processes that characterize thinking: “System 1” is a fast decision making system responsible for intuitive decision making based on emotions, vivid imagery, and associative memory. “System 2” is a slow system that observes System 1’s outputs, and intervenes when “intuition” is insufficient. Such an interventi...

An agent achieves its goals by interacting with its environment, cyclically choosing and executing suitable actions. An action execution process is a reasonable and critical part of an entire cognitive architecture, because the process of generating executable motor commands is not only driven by low-level environmental information, but is also ini...

High-dimensional vector spaces have noteworthy properties that make them attractive for representation models. A reduced description model is a mechanism for encoding complex structures as single high-dimensional vectors. Moreover, these vectors can be used to directly process complex operations such as analogies, inferences, and structural compari...

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We...

A global workspace is a hub of binding and propagation in a population of loosely coupled signaling elements. Global workspace (GW) architectures recruit many distributed, specialized agents to help resolve focal ambiguities. In the brain, conscious experiences may reflect a global workspace function. For animals the natural world is full of fitnes...

Sparse distributed memory is an auto-associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM, the Integer SDM that uses modular arithmetic integer vectors rather than binary vectors. This extension preserves many of the desirable properties of the original SDM: auto-associativity, con...

Significant debate on fundamental issues remains in the subfields of cognitive science, including perception, memory, attention, action selection, learning, and others. Psychology, neuroscience, and artificial intelligence each contribute alternative and sometimes conflicting perspectives on the supervening problem of artificial general intelligenc...

Human spatial representations are known to be remarkably robust and efficient, and to be structured hierarchically. In this paper, we describe a biologically inspired computational model of spatial working memory attempting to account for these properties, based on the LIDA cognitive architecture. We also present preliminary results regarding a virt...

We describe a cognitive architecture (LIDA) that affords attention, action selection and human-like learning intended for use in controlling cognitive agents that replicate human experiments as well as performing real-world tasks. LIDA combines sophisticated action selection, motivation via emotions, a centrally important attention mechanism, and m...

Editors: Włodzisław Duch / Ah-Hwee Tan / Stan Franklin

Biologically inspired cognitive architectures should faithfully model the high-level modules and processes of cognitive neuroscience. Also, they are expected to contribute to the BICA “challenge of creating a real-life computational equivalent of the human mind”. One important component of the mind is attention and attentional learning. In this pap...

Artificial intelligence (AI) initially aimed at creating “thinking machines,” that is, computer systems having human level general intelligence. However, AI research has until recently focused on creating intelligent, but highly domain-specific, systems. Currently, researchers are again undertaking the original challenge of creating AI systems (age...

A biologically inspired cognitive architecture must draw its insights from what is known from animal (including human) cognition. Such architectures should faithfully model the high-level modules and processes of cognitive neuroscience. Also, biologically inspired cognitive architectures are expected to contribute to the BICA ‘‘challenge of creatin...

Sparse distributed memory (SDM) is an auto-associative memory system that stores high-dimensional Boolean vectors. SDM uses the same vector for the data (word) and the location where it is stored (address). Here, we present an extension of the original SDM that uses word vectors of larger size than address vectors. This extension preserves many of...

The attentional blink (AB) refers to the impairment in consciously perceiving the second of two targets presented in close temporal proximity (200 – 500ms) in a rapid serial visual presentation paradigm. The present paper is a preliminary report describing a conceptual and partially computational model of the AB based on the LIDA (Learning Intellig...

Time perception and inferences there from are of critical importance to many autonomous agents. But time is not perceived directly by any sensory organ. We argue that time is constructed by cognitive processes. Here we present a model for time perception that concentrates on succession and duration, and that generates these concepts and others, suc...

Sparse distributed memory is an auto-associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM, the Integer SDM that uses modular arithmetic integer vectors rather than binary vectors. This extension preserves many of the desirable properties of the original SDM: auto-associativity, con...

This position paper explores the possible contributions to the science of psychology from insights obtained by building and experimenting with cognitive robots. First, the functional modeling characteristic of experimental psychology is discussed. Second, the computational modeling required for cognitive robotics is described, and possible experime...

Intelligent software agents aiming for general intelligence are likely to be exceedingly complex systems and, as such, will be difficult to implement and to customize. Frameworks have been applied successfully in large-scale software engineering applications. A framework constitutes the skeleton of the application, capturing its generic functional...

Although it is a relatively new field of study, the animal cognition literature is quite extensive and difficult to synthesize. This paper explores the contributions a comprehensive, computational, cognitive model can make toward organizing and assimilating this literature, as well as toward identifying important concepts and their interrelations....

What roles or functions does consciousness fulfill in the making of moral decisions? Willartificial agents capable of making appropriate decisions in morally charged situations requiremachine consciousness? Should the capacity to make moral decisions be considered an attributeessential for being designated a fully conscious agent? Research on the pro...

Medical diagnosis is accomplished by a set of complex cognitive processes requiring the iterative application of abduction, deduction, and induction. Previous research in computational modeling of medical diagnosis has had only limited success by defining sub-domains that offer a computationally tractable problem. However, the aspect of diagnostic...

We propose that human cognition consists of cascading cycles of recurring brain events. Each cognitive cycle senses the current situation, interprets it with reference to ongoing goals, and then selects an internal or external action in response. While most aspects of the cognitive cycle are unconscious, each cycle also yields a momentary "ignition...

A dream of humanoid robot researchers is to develop a complete “human-like” (whatever that means) artificial agent both in terms of body and brain. We now have seen an increasing number of humanoid robots (such as Honda's ASIMO, Aldebaran's Nao and many others). These, however, display only a limited number of cognitive skills in terms of perceptio...

The several different memory systems in human beings play crucial roles in facilitating human cognition. To build artificial agents that have cognitive capabilities similar to those of human beings, we have to develop these agents based on architectures modelling what we know of human cognition from neuroscience, psychology and cognitive science. I...

Philosophers, psychologists and neuroscientists have proposed various forms of a "self" in humans and animals. All of these selves seem to have a basis in some form of consciousness. The Global Workspace Theory (GWT) [1 -3] suggests a mostly unconscious, many layered self-system. In this paper we consider several issues that arise from attempts to...

Medical diagnosis is accomplished by a set of complex cognitive processes requiring the iterative application of abduction, deduction, and induction. Previous research in computational modeling of medical diagnosis has had only limited success by defining sub-domains that offer a computationally tractable problem. However, the aspect of diagnostic...

Autonomous mobile robots require efficient control of their movement. There are several very good approaches for controlling autonomous robots under bound conditions; how-ever, self-adaptation to dynamic environments is very complicated. This paper focuses on part of an autonomous mobile robot prototype named FIC (Fluent Interactive Codelets framew...

Sparse distributed memory is an auto-associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM that uses word vectors of larger size than address vectors. This extension preserves many of the desirable properties of the original SDM: Auto-associability, content addressability, distribut...

One aspect of human intelligence is its ability to achieve goals by devising unexpected and even creative solutions to problems that have never before been encountered. This ability of exploring and constructing solutions to non-routine problems is central to the development of our sciences and technologies. Replicating Non-Routine Problem Solving...

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. Th...

Intelligent software agents (agents) adhering to the action selection paradigm have only one primary task that they need accomplish at any given time: to choose their next action. Consequently, modeling the current situation effectively is a critical task for any agent. With an accurate model of the current situation, actions can be better selected...

Cognitive theories of consciousness should provide effective frameworks to implement machine consciousness. The Global Workspace Theory is a leading theory of consciousness which postulates that the primary function of consciousness is a global broadcast that facilitates recruitment of internal resources to deal with the current situation as well a...

We argue that the functions of consciousness are implemented in a bio-computational manner. That is to say, the conscious as well as the non-conscious aspects of human thinking, planning, and perception are produced by adaptive, biological algorithms. We propose that machine consciousness may be produced by similar adaptive algorithms running on th...

The currently leading cognitive theory of consciousness, Global Workspace Theory,1,2 postulates that the primary functions of consciousness include a global broadcast serving to recruit internal resources with which to deal with the current situation and to modulate several types of learning. In addition, conscious experiences present current condi...

Particular features of the signaling characteristics of the scent marks of temperate zone, seasonally breeding mammals may reflect differences in their reproductive state and, hence, be variable. Consequently, an individual’s perception of self may depend more on the condition independent than on the condition-dependent signaling characteristics of...

IntroductionGlobal Workspace TheoryVoluntary and Non-Voluntary Memories“Conscious” Software AgentsThe IDA ArchitectureThe IDA Cognitive CycleIdeomotor Theory and Its Implementation as Volition in IDAVoluntary Versus Non-Voluntary Episodic Memories in Humans and in IDAWanted Versus Unwanted Non-Voluntary Memories in Humans and in IDAConclusion Notes...

Some non-human animals may possess the ability to recall the "what", "where", and "when" of a single past event. We tested the hypothesis that male meadow voles possess the capacity to recall the "what", "where", and "when" of a single past event associated with mate selection in two experiments. Briefly, male voles were allowed to explore an appar...

Every agent aspiring to human level intelligence, every AGI agent, must be capable of a theory of mind. That is, it must be able to attribute mental states, including intentions, to other agents, and must use such attributions in its action selection process. The LIDA conceptual and computational model of cognition offers an explanation of how theo...

While neural net models have been developed to a high degree of sophistication, they have some drawbacks at a more integrative, "architectural" level of analysis. We describe a "hybrid" cognitive architecture that is implementable in neuronal nets, and which has uniform brainlike features, including activation-passing and highly distributed "codele...

Implementing and fleshing out a number of psychological and neuroscience theories of cognition, the LIDA conceptual model aims at being a cognitive “theory of everything.” With modules or processes for perception, working memory, episodic memories, “consciousness,” procedural memory, action selection, perceptual learning, episodic learning, deliber...

During his talk at the 2006 AGI Workshop, Stan Franklin suggested that his LIDA architecture might fruitfully be considered not only as a specific AGI design, but also as a general framework within which to discuss and compare various AGI designs and approaches. With this in mind, following the workshop itself, Ben Goertzel formulated a list of sim...

At the end of the 2006 AGI Workshop, a number of presenters were invited to participate in a panel discussion on the theme “What Are the Bottlenecks, and How Soon to AGI?” This chapter presents a record of that dialogue, including audience participation, lightly edited by the presenters themselves for greater readability.

In this paper, we present LIDA, a working model of, and theoretical foundation for, machine consciousness. LIDA's architecture and mechanisms were inspired by a variety of computational paradigms and LIDA implements the Global Workspace Theory of consciousness. The LIDA architecture's cognitive modules include perceptual associative memory, episodi...

This chapter aims to provide an overview of existing computational (mechanistic) mod- els of cognition in relation to the study of consciousness, on the basis of psychologi- cal and philosophical theories and data. It examines various mechanistic explanations of consciousness in existing computational cognitive models. Serving as an example for the...

This paper embodies the authors' suggestive, hypothetical and sometimes speculative attempts to answer questions related to the interplay between consciousness and AI. We explore the theoretical foundations of consciousness in AI systems. We provide examples that demonstrate the potential utility of incorporating functional consciousness in cogniti...

The IDA model of cognition is a fully integrated artificial cognitive system reaching across the full spectrum of cognition, from low-level perception/action to high-level reasoning. Extensively based on empirical data, it accurately reflects the full range of cognitive processes found in natural cognitive systems. As a source of plausible explanat...

“And as soon as I had recognized the taste of the piece of madeleine soaked in her decoction of lime-blossom which my aunt used to give me ... immediately the old grey house upon the street, where her room was, rose up like a stage set to attach itself to the little pavilion opening on to the garden which had been built out behind it for my parents...

This paper describes the integration of several cognitively inspired anticipation and anticipatory learning mechanisms in an autonomous agent architecture, the Learning Intelligent Distribution Agent (LIDA) system. We provide computational mechanisms and experimental simulations for variants of payoff, state, and sensorial anticipatory mechanisms....

This is a report on the LIDA architecture, a work in progress that is based on IDA, an intelligent, autonomous, "conscious" software agent that does personnel work for the US Navy. IDA uses locally developed cutting edge artificial intelligence technology designed to model hu- man cognition. IDA's task is to find jobs for sailors whose current assi...

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, human-like learning...

In this paper we attempt to develop mechanisms for procedural memory and procedural learning for cognitive robots on the basis of what is known about the same facilities in humans and animals. The learning mechanism will provide agents with the ability to learn new actions and action sequences with which to accomplish novel tasks.

Abstract This paper presents research on the,development,of effective forgetting mechanisms ,for the Sparse Distributed Memory (SDM) system, to computationally model Transient Episodic Memory (TEM), a short-term sensory perceptual episodic memory,in software agents. Possible theories and mechanisms for forgetting are retrieval failures, decay and i...