This paper proposes a model for an artificial autonomous moral agent (AAMA), which is parsimonious in its ontology and minimal in its ethical assumptions. Starting from a set of moral data, this AAMA is able to learn and develop a form of moral competency. It resembles an “optimizing predictive mind,” which uses moral data (describing typical behavior of humans) and a set of dispositional traits to learn how to classify different actions (given a given background knowledge) as morally right, wrong, (...) or neutral. When confronted with a new situation, this AAMA is supposedly able to predict a behavior consistent with the training set. This paper argues that a promising computational tool that fits our model is “neuroevolution,” i.e. evolving artificial neural networks. (shrink)

The DSM-III, DSM-IV, DSM-IV-TR and ICD-10 have judiciously minimized discussion of etiologies to distance clinical psychiatry from Freudian psychoanalysis. With this goal mostly achieved, discussion of etiological factors should be reintroduced into the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. A research agenda for the DSM-V advocated the "development of a pathophysiologically based classification system". The author critically reviews the neuroevolutionary literature on stress-induced and fear circuitry disorders and related amygdala-driven, species-atypical fear behaviors of clinical severity in adult (...) humans. Over 30 empirically testable/falsifiable predictions are presented. It is noted that in DSM-IV-TR and ICD-10, the classification of stress and fear circuitry disorders is neither mode-of-acquisition-based nor brain-evolution-based. For example, snake phobia and dog phobia are clustered together. Similarly, research on blood-injection-injury-type-specific phobia clusters two fears different in their innateness: 1) an arguably ontogenetic memory-trace-overconsolidation-based fear and 2) a hardwired fear of the sight of one's blood or a sharp object penetrating one's skin. Genetic architecture-charting of fear-circuitry-related traits has been challenging. Various, non-phenotype-based architectures can serve as targets for research. In this article, the author will propose one such alternative genetic architecture. This article was inspired by the following: A) Nesse's "Smoke-Detector Principle", B) the increasing suspicion that the "smooth" rather than "lumpy" distribution of complex psychiatric phenotypes may in some cases be accounted for by oligogenic transmission, and C) insights from the initial sequence of the chimpanzee genome and comparison with the human genome by the Chimpanzee Sequencing and Analysis Consortium published in late 2005. Neuroevolutionary insights relevant to fear circuitry symptoms that primarily emerge overconsolidationally are presented. Also introduced is a human-evolution-based principle for clustering innate fear traits. The "Neuroevolutionary Time-depth Principle" of innate fears proposed in this article may be useful in the development of a neuroevolution-based taxonomic re-clustering of stress-triggered and fear-circuitry disorders in DSM-V. Four broad clusters of evolved fear circuits are proposed based on their time-depths: 1) Mesozoic circuits hardwired by wild-type alleles driven to fixation by Mesozoic selective sweeps; 2) Cenozoic circuits relevant to many specific phobias; 3) mid Paleolithic and upper Paleolithic circuits ; 4) Neolithic circuits. More importantly, the author presents evolutionary perspectives on warzone-related PTSD, Combat-Stress Reaction, Combat-related Stress, Operational-Stress, and other deployment-stress-induced symptoms. The Neuroevolutionary Time-depth Principle presented in this article may help explain the dissimilar stress-resilience levels following different types of acute threat to survival of oneself or one's progency. PTSD rates following exposure to lethal inter-group violence are usually 5-10 times higher than rates following large-scale natural disasters such as forest fires, floods, hurricanes, volcanic eruptions, and earthquakes. The author predicts that both intentionally-caused large-scale bioevent-disasters, as well as natural bioevents such as SARS and avian flu pandemics will be an exception and are likely to be followed by PTSD rates approaching those that follow warzone exposure. During bioevents, Amygdala-driven and locus-coeruleus-driven epidemic pseudosomatic symptoms may be an order of magnitude more common than infection-caused cytokine-driven symptoms. Implications for the red cross and FEMA are discussed. It is also argued that hospital phobia as well as dog phobia, bird phobia and bat phobia require re-taxonomization in DSM-V in a new "overconsolidational disorders" category anchored around PTSD. The overconsolidational spectrum category may be conceptualized as straddling the fear circuitry spectrum disorders and the affective spectrum disorders categories, and may be a category for which Pitman's secondary prevention propranolol regimen may be specifically indicated as a "morning after pill" intervention. Predictions are presented regarding obsessive-compulsive disorder and "culture-bound" acute anxiety symptoms. Also discussed are insights relevant to pseudoneurological symptoms and to the forthcoming Dissociative-Conversive disorders category in DSM-V, including what the author terms fright-triggered acute pseudo-localized symptoms. Speculations based on studies of the human abnormal-spindle-like, microcephaly-associated gene, the microcephaly primary autosomal recessive gene, and the forkhead box p2 gene are made and incorporated into what is termed "The pre-FOXP2 Hypothesis of Blood-Injection-Injury Phobia." Finally, the author argues for a non-reductionistic fusion of "distal neurobiology" with clinical "proximal neurobiology," utilizing neurological heuristics. It is noted that the value of re-clustering fear traits based on behavioral ethology, human-phylogenomics-derived endophenotypes and on ontogenomics can be confirmed or disconfirmed using epidemiological or twin studies and psychiatric genomics. (shrink)

The function of the brain is intricately woven into the fabric of time. Functions such as (i) storing and accessing past memories, (ii) dealing with immediate sensorimotor needs in the present, and (iii) projecting into the future for goal-directed behavior are good examples of how key brain processes are integrated into time. Moreover, it can even seem that the brain generates time (in the psychological sense, not in the physical sense) since, without the brain, a living organism cannot have the (...) notion of past nor future. When combined with an evolutionary perspective, this seemingly straightforward idea that the brain enables the conceptualization of past and future can lead to deeper insights into the principles of brain function, including that of consciousness. In this paper, we systematically investigate, through simulated evolution of artificial neural networks, conditions for the emergence of past and future in simple neural architectures, and discuss the implications of our findings for consciousness and mind uploading. (shrink)