Memory evolved to supply useful, timely information to the organism’s decision-making systems. Therefore, decision rules, multiple memory systems, and the search engines that link them should have coevolved to mesh in a coadapted, functionally interlocking way. This adaptationist perspective suggested the scope hypothesis: When a generalization is retrieved from semantic memory, episodic memories that are inconsistent with it should be retrieved in tandem to place boundary conditions on the scope of the generalization. Using a priming paradigm and a decision task involving person memory, the authors tested and confirmed this hypothesis. The results support the view that priming is an evolved adaptation. They further show that dissociations between memory systems are not—and should not be—absolute: Independence exists for some tasks but not others. Memory is a gift of nature, the ability of living organisms to retain and to utilize acquired information or knowledge.... Owners of biological memory systems are capable of behaving more appropriately at a later time because of their experiences at an earlier time, a feat not possible for organisms without memory. (Tulving, 1995a, p. 751) If there is one proposition on which all psychologists seem to

This paper addresses the relationship between social intelligence and narrative intelligence, with a particular emphasis on 1) the phylogenetic origins of primate (narrative) intelligence, and 2) the ontogenetic origin of autobiographical stories. The `Narrative Intelligence Hypothesis` (NIH) is introduced according to which the evolutionary origin of stories and narrativity was correlated with increasing social dynamics in primate societies, in particular the need to communicate about third-party relationships. Requirements for artificial socially intelligent story-tellers are outlined, and the issue of testing social intelligence is discussed.

The author reviews reemerging coconstructive conceptions of development and recent empirical findings of developmental plasticity at different levels spanning several fields of developmental and life sciences. A cross-level dynamic biocultural coconstructive framework is endorsed to understand cognitive and behavioral development across the life span. This framework integrates main conceptions of earlier views into a unifying frame, viewing the dynamics of life span development as occurring simultaneously within different time scales (i.e., moment-to-moment microgenesis, life span ontogeny, and human phylogeny) and encompassing multiple levels (i.e., neurobiological, cognitive, behavioral, and sociocultural). Viewed through this metatheoretical framework, new insights of potential interfaces for reciprocal cultural and experiential influences to be integrated with behavioral genetics and cognitive neuroscience research can be more easily prescribed. Metaphorically speaking, two related pendulums, one swinging back and forth from nature to nurture and the other from brain to mind, have been running the clocks of developmental and cognitive inquiries for centuries. Instead of polarizing toward either end, this review of recent advances in life and developmental sciences

This article discusses narrative intelligence in the context of the evolution of primate (social) intelligence, and with respect to the particular cognitive limits that constrain the development of human social networks and societies.

Abstract. It has been widely acknowledged in the areas of human memory and cognition that behaviour and emotion are essentially grounded by autobiographic knowledge. In this paper we propose an overall framework of human autobiographic memory for modelling believable virtual characters in narrative story-telling systems and role-playing computer games. We first lay out the background research of autobiographic memory in Psychology, Cognitive Science and Artificial Intelligence. Our autobiographic agent framework is then detailed with features supporting other cognitive processes which have been extensively modelled in the design of believable virtual characters (e.g. goal structure, emotion, attention, memory schema and reactive behaviour-based control at a lower level). Finally we list directions for future research at the end of the paper.

The paper presents the outlines of a general, multidisciplinary theory of meaning based on the concept of value as a biological and social category, synthesizing ideas from biologically oriented psychology, semiotics and cybernetics. The theory distinguishes between four types of meaning systems: cue-based, association-based, icon-based and symbol-based, forming an evolutionary and epigenetic hierarchy. This hierarchy is applied to phylogenetic and ontogenetic development, pointing out significant parallels between the two, involving both continuity and discontinuity between different levels, i.e. meaning systems. The theory is finally applied to the field of developing intelligent artificial autonomous systems, showing grave limitations in existing systems and suggesting guidelines for future work.

In this paper, we introduce an ongoing research project, which aims at developing an immersive storytelling environment. In such a system, which is inspired from the "Holodeck" device, human users will be able to interact with artificial actors through speech, while sharing the same physical environment. Once on the set, the users will be able to participate in story generation by influencing virtual actors or altering the common environment. An essential aspect is that user involvement will not have to be permanent, and that the users will be allowed to leave the set to watch the story unfold in their absence and to return at a later stage. We discuss some fundamental AI problems with which the implementation will be faced and relate them to narrative theories and models of storytelling. More specifically, we describe how users can interfere with the virtual actor's plans to influence story generation in terms of interaction 1.

Abstract. According to traditional animators, the art of building believable characters resides in the ability to successfully portray a character’s behaviour as the result of its internal emotions, intentions and thoughts. Following this direction, we want our agents to be able to explicitly talk about their internal thoughts and report their personal past experiences. In order to achieve it, we look at a specific type of episodic long term memory. This paper describes the integration of Autobiographic Memory into FAtiMA, an emotional agent architecture that generates emotions from a subjective appraisal of events. 1

www.elsevier.com/locate/dr The authors review competing theories concerning the emergence and early development of autobiographical memory. It is argued that the differences between these accounts, although important, may be more apparent than real. The crux of these disagreements lies not in what processes are important, but rather, the role these different processes play in the emergence of autobiographical memory and the temporal primacy of these controlling variables. These differences are explored theoretically and then extant as well as new data are brought to bear on these issues. What emerges is a new, more inclusive, multifactorial framework that integrates the controlling variables from diverse perspectives providing a more complete account of the beginnings of autobiographical memory.

Abstract — This work proposes an initial memory model for a long-term artificial companion, which migrates among virtual and robot platforms based on the context of interactions with the human user. This memory model enables the companion to remember events that are relevant or significant to itself or to the user. For other events which are either ethically sensitive or with a lower long-term value, the memory model supports forgetting through the processes of generalisation and memory restructuring. The proposed memory model draws inspiration from the human short-term and long-term memories. The short-term memory will support companions in focusing on the stimuli that are relevant to their current active goals within the environment. The long-term memory will contain episodic events that are chronologically sequenced and derived from the companion’s interaction history both with the environment and the user. There are two key questions that we try to address in this work: 1) What information should the companion remember in order to generate appropriate behaviours and thus smooth the interaction with the user? And, 2) What are the relevant aspects to take into consideration during the design of memory for a companion that can have different types of virtual and physical bodies? Finally, we show an implementation plan of the memory model, focusing on issues of information grounding, activation and sensing based on specific hardware platforms. I.