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Evolutionary epistemology versus faith and justified true belief: ― Does science work and can we know the truth? William P. Hall President Kororoit Institute.

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Presentation on theme: "Evolutionary epistemology versus faith and justified true belief: ― Does science work and can we know the truth? William P. Hall President Kororoit Institute."— Presentation transcript:

1 Evolutionary epistemology versus faith and justified true belief: ― Does science work and can we know the truth? William P. Hall President Kororoit Institute Proponents and Supporters Assoc., Inc. - Atheists Society Lecture: 12 August 2014 Access my research papers from Google Citations Google Citations

2 Introduction Epistemology is a lot more important than a subject for philosophical debate Humanity faces a range of existential risks, e.g., – Anthropogenic global warming & climate change Rising sea levels Global crop failures (e.g., potato famines) Exotic disease pandemics (e.g., ebola) – Peak oil / minerals – Global scale catastrophe 1851-scale electromagnetic storms Meteor strike How do we know this? What should we do about them: How do we know what we think we know? Who do we trust? Does science provide truth? Or a suitable basis for rational action? 2

3 Faith and belief do not provide effective answers!

4 9/11 & horrors of the 20 th Century The 9/11 attacks on the World Trade Center Often suicidally committed perpetrators can be guided by one or a few charismatic leaders to commit massive outrages against initially comparatively peaceful populations – Hitler, WWII in Europe and the Holocaust – Japan's warlords and WWII in the Pacific – Stalin, terrors and gulags – Mao Tse Tung and the Cultural Revolution – The multitude of smaller "ethnic cleansings" in the Balkans/Cambodia/Iraq/Iran/Sudan etc… 4

5 Some smaller consequences of extreme beliefs Historic – some smaller examples self-inflicted death – Joseph Kibweteere's Catholic-based Movement for the Restoration of the Ten Commandments of God (2000 – deaths in Uganda from immolation.). See Venter Doomsday movements in Africa: Restoration of the Ten Commandments of God)Doomsday movements in Africa: Restoration of the Ten Commandments of God – Marshall Herff Applewhite's Heaven's Gate Cult ( poisoned). See Zeller (2003). The euphemization of violence: The case of Heaven’s Gate”.The euphemization of violence: The case of Heaven’s Gate – Jim Jones "Jonestown Massacre" ( deaths in Guyana, mostly from suicide or murder of children (217) by parents). See Alternative Considerations of Jonestown & Peoples TempleJonestown Massacre Alternative Considerations of Jonestown & Peoples Temple Current – Suicide bombers and the Sunni-Shia conflict, murder and mayhem reported on a daily basis 5

6 How do individual people become weapons of mass destruction? Contexts: – Psychotic leaders radiating ultimate conviction – Followers’ willingness to abdicate thoughtful responsibility for own actions Charismatic leaders who convince others they have special powers, such as the ability to heal, to speak with God directly, or know absolute truth Willingness to accept on faith (and faith alone) the word of God as proclaimed by some charismatic leader or some purported holy document Big question: – What leads seemingly ordinary people to sacrifice their property and lives to follow charismatic leaders? – Easier to accept and believe than to think and criticize 6

7 Cults and the primacy of true belief Con jobs performed by almost all religions and cults based on faith and belief Sola fide (by faith alone - see Wikipedia)Wikipedia – God's pardon for guilty sinners is granted to and received through faith, conceived as excluding all "works," alone. – True belief is determined by faith and faith alone Faith in the guru/leader Faith in the designated scriptures Some will claim confirmatory manifestations to justify true belief or one disconfirmatory case to deny the vast bulk of evidence – Far better to criticize all important claims How can we combat the Murdoch press?? 7

8 My personal problematic “Your work is not scientific” Hall, W.P Comparative population cytogenetics, speciation and evolution of the iguanid lizard genus Sceloporus. PhD Thesis, Harvard UniversityComparative population cytogenetics, speciation and evolution of the iguanid lizard genus Sceloporus Invited review: Hall, W.P Chromosome variation, genomics, speciation and evolution in Sceloporus lizards. Cytogenetic and Genome Research 127 (2-4), pp Chromosome variation, genomics, speciation and evolution in Sceloporus lizards

9 Why understanding epistemology became personally important to me (Evolutiononary biology is not a physical science) PhD Harvard (1973) Chromosome variation, genomics, speciation and evolution in Seceloporus lizards (cty.) Ernest E Williams & Ernst MayrChromosome variation, genomics, speciation and evolution in Seceloporus lizards – One of the largest studies of chromosome variation to then – Novel theories challenging Mayr’s geographical speciation model Poorly received by my advisors, journals & other critics – Referring to my draft thesis, EEW said, “I don’t like it, do it over! ” [i.e., the thesis, not the research] – [Me] What’s wrong with it? [EEW] “I don’t know.” – The data was so overwhelming he and Mayr still had to pass the work In while I was a post doc at Univ. Melbourne I summarised my thesis work for peer review and formal publication:formal publication – A U. of Mich. PhD student who earlier assisted both in the field and lab claimed “Your work is unscientific” and re-drafted it – He failed to understand the logic of my methodology and argument – Was he correct? I spent most of postdoc studying history and epistemology of science – Too late for my job prospects as an evolutionary biologist 9

10 Initial learnings from history and philosophy of science (< 1980) Most philosophers seemed to live in ivory towers, away with the black swans and other figments of imagination Only two offered practical answers to my problematic (ref Maniglier on Bachelard and the concept of problematic) Maniglier on Bachelard and the concept of problematic – Thomas Kuhn (1970), The Structure of Scientific Revolutions Historical and sociological analysis Paradigms Normal vs Revolutionary Science (Kuhn helped my understanding, but not relevant for today’s talk) – Karl Popper (1959)The Logic of Scientific Discovery (1963)Conjectures and Refutations: the Growth of Scientific Knowledge (1972) Objective Knowledge: An Evolutionary Approach (1977 – with J.C. Eccles) The Self and Its Brain: An Argument for Interactionism (1994)Knowledge and the Body-Mind Problem: In Defence of Interaction 10

11 Popper 1959, 1963 – We can’t prove if we know the truth – There is no such thing as induction – Deductively falsifying a theory is deterministic – Correspondence theory of truth – Make bold hypotheses and try to falsify them – what is left is better than what has been falsified – Falsifiability demarcates science from pseudoscience Popper (1972 – “Objective Knowledge”) biological approach – Knowledge is a biological phenomenon – Knowledge is solutions to problems of life – All knowledge is cognitively constructed (Popper is a radical constructivist!) – Falsification doesn’t work in the real world; claims can be protected by auxiliary hypotheses (All claims to know must be regarded as fallible) – Three worlds ontology – “Tetradic schema” / “general theory of evolution” to eliminate errors and build knowledge Many contemporary philosophers misunderstand Objective Knowledge – “Objective knowledge” = knowledge codified into/onto a physical object (DNA, printed paper, pitted CD, magnetic domains) The early Popper vs. the mature Popper on epistemology 11

12 How do you do “science” with complex and often chaotic systems? Differences between the life and physical sciences – Deterministic vs stochastic (≠ indeterminate) causation – Physical science Hypothetico-deductive approaches Theoretical predictions susceptible to near deterministic refutation – Living systems Causally complex, non-linear, to some degree chaotic Can explain retrodictively but cannot predict deterministically Comparative approach – Study “natural experiments” Shared common ancestry controls most variables Look for correlations between possible causes and effects – Cycles of speculation, criticism and testing Extend scope phylogenetically and range of effects – Hall (1983) Modes of speciation and evolution in the sceloporine iguanid lizards. I. Epistemology of the comparative approach and introduction to the problemModes of speciation and evolution in the sceloporine iguanid lizards. I. Epistemology of the comparative approach and introduction to the problem 12

13 1.PROBLEM IDENTIFICATION AND INITIAL SPECULATIONS 2. SELECT APPROPRIATE NATURAL ‘EXPERIMENTS’ AND ‘CONTROLS’ TO ILLUSTRATE PROBLEM 3.COLLECT DATA FROM EXPERIMENTS AND CONTROLS 4.DO CROSS-CORRELATION ANALYSES OF N-DIMENSIONAL MATRICES TO IDENTIFY SIGNIFICANT PHENOMENA 5.GENERATE MODELS THROUGH ANALOGY, INDUCTION, ETC. WHICH PROVIDE CAUSAL EXPLANATIONS FOR SIGNIFICANTLY CORRELATED PHENOMENA ARE CORRELATIONS FOUND ? 6. IS MODEL LOGIC OK? SHOULD MATRICES BE RE- RANKED ? 6a. IS MODEL LOGIC OK? 8. TEST PREDICTIONS: a.SAME PHENOMENA OF NEW CASES b.OTHER PHENOMENA OF ORIGINAL CASES c.OTHER PHENOMENA OF OTHER CASES 3a.COLLECT OTHER NEEDED DATA 4a.FURTHER CROSS CORRELATION ANALYSES WITH NEW DATA 5a.REVISE AND/OR REPLACE MODEL AS INDICATED BY NEW CORRELATION ANALYSES 9. TEST RECONSTRUCTIONS: DO MODELS PLAUSIBLY RECONSTRUCT CASES ACCORDING TO EVIDENCE? 7. TEST ASSMPTIONS: a.DEMONSTRATIONS b.H D EXPERIMENTS c.SIMULATIONS OK ? OK ? OK ? AND 10.A NATURAL PHENOMENON HAS BEEN IDENTIFIED AND UNDERSTOOD, BUT THIS UNDERSTANDING SHOULD BE HELD ONLY AS LONG AS IT PROVIDES REALISTIC EXPLANATIONS OF OBSERVATIONS ABOUT NATURE NO YES NO My answer to the problematic: How to understand complex stochastic systems scientifically? Build, test & criticize as as many connections as possible between theory and reality 13

14 Scientific thinking in the 20 th Century (skipped for today) See extra slides See extra slides

15 Evolutionary epistemology ― A biologically-based theory of the growth of scientific knowledge

16 Philosophy, “knowledge”, and “truth” A-priori assumptions – There is a “real world” with law-like behaviours – The physics of reality causes individual existences – There are no essences beyond the reality of our existences – Solipsistic approaches are self-defeating A claim to know may truly correspond to reality, but… Truth (or falsity) in the real world cannot be proved – Knowledge of the world is not identical to the real world – Cognition is in the world - it does not mirror it 16

17 Problems – “Problem of Induction” - any number of confirmations does not prove the next test will not be a refutation (e.g., Gettier) – The biological impossibility to know if a claim to know is true Vision does not form an image of external reality The brain does not perceive reality, it constructs a model – Perception and cognition are consequences of propagating action potentials in a neural network. – Action potentials stimulated by physical perturbations to neurons – Perception lags reality (see added slides)added slides Knowledge is constructed Impossible to know whether a claim is true or not 17 Clock, via Wikimedia

18 Popper’s probable sources for his biological approach to epistemology 18 Charles Darwin (1859) On the Origin of Species Konrad Lorenz – 1973 Nobel Prize (animal cognition and knowledge) Donald T. Campbell cognitive scientist concerned with knowledge growth – (1960) Blind Variation and Selective Retention…. (paper) – (1974) Evolutionary Epistemology (chapter) Popper’s acknowledgements, e.g., – (1972) Knowledge is solutions to problems of life – (1974) “The main task of the theory of knowledge is to understand it as continuous with animal knowledge; and … its discontinuity – if any – from animal knowledge” [p 1161, “Replies to my Critics” in The Philosophy of Karl Popper]

19 Karl Popper's first big idea from Objective Knowledge: “three worlds” ontology 19 Energy flow Thermodynamics Physics Chemistry Biochemistry Cybernetic self-regulation Cognition Consciousness Tacit knowledge Genetic heredity Recorded thought Computer memory Logical artifacts Explicit knowledge Encode/Reproduce Recall/Decode/Instruct Enable/Constrain Regulate/Control Inferred logic Describe/Predict Test Observe World 1 Existence/Reality World 2 World of mental or psychological states and processes, subjective experiences, memory of history Organismic/personal/situational/ subjective/tacit knowledge in world 2 emerges from interactions with world 1 World 3 The world of “objective” knowledge Produced / evaluated by world 2 processes “living knowledge” “codified knowledge” “life”

20 “Epistemic cut” concept clarifies validity and relationships of Popper’s three worlds Popper did not physically justify his ontological proposal Howard Pattee 1995 “Artificial life needs a real epistemology” – An “epistemic cut” (also known as “Heisenberg cut”) refers to strict ontological separation in both physical and philosophical senses between: Knowledge of reality from reality itself, e.g., description from construction, simulation from realization, mind from brain [or cognition from physical system]. Selective evolution began with a description-construction cut.... The highly evolved cognitive epistemology of physics requires an epistemic cut between reversible dynamic laws and the irreversible process of measuring [or describing]…. – Different concept from “epistemic gap” separating “phenomenological knowledge” from “physical knowledge” – No evidence Pattee or Popper ever cited the other One epistemic cut separates the blind physics of world 1 from the cybernetic self-regulation, cognition, and living memory of world 2 A second epistemic cut separates the self-regulating dynamics of living entities from the knowledge encoded in books, computer memories and DNAs and RNAs See Pattee (2012) Laws, Language and Life. Biosemiotics vol. 7 20

21 Popper’s second big idea: "tetradic schema“ / "evolutionary theory of knowledge" / "general theory of evolution" 21 P n a real-world problem faced by a living entity TS a tentative solution/theory. Tentative solutions are varied through serial/parallel iteration EE a test or process of error elimination P n+1 changed problem as faced by an entity incorporating a surviving solution The whole process is iterated  TSs may be embodied in W2 “structure” in the individual entity, or  TSs may be expressed in words as hypotheses in W3, subject to objective criticism; or as genetic codes in DNA, subject to natural selection  Objective expression and criticism lets our theories die in our stead  Through cyclic iteration, sources of errors are found and eliminated  Tested solutions/theories become more reliable, i.e., approach reality  Surviving TSs are the source of all knowledge! Popper (1972), pp

22 22 USAF Col. John Boyd's OODA Loop process wins dogfights and military conflicts Achieving strategic power depends critically on learning more, better and faster, and reducing decision cycle times compared to competitors. See Osinga (2005) Science, strategy and war: the strategic theory of John Boyd -

23 23 Some OODA definitions after John Boyd Generic process for any complex adaptive entity – Observation assembles data about the world (including the entity's own prior effects and those of its competitors on that world). Data is given context relating to interactions with the world. – Orientation processes information from those observations into semantically linked knowledge to form a world view comprised of recent observations memories of prior experience (which may be explicit, implicit or even tacit) genetic heritage (i.e., "natural talent") cultural traditions (i.e., paradigms) sense making (i.e., inferring meaning) analysis (destruction) of the existing world view synthesis (creation) of a revised world view including possibilities for action. This generates intelligence (in a military sense). – Decision selects amongst possible actions generated by the orientation, action(s) to try. Choice is governed and informed by wisdom based on experience gained from previous OODA cycles – Action puts tests decisions against the world. The loop begins to repeat as the entity observes the results of its action.

24 24 Popper's General Theory of Evolution + John Boyd O = Observation of reality; O = Making sense and orienting to observations with solutions to be tested; D = Selection of a solution or making a “decision” A = Application of decision or "Action" on reality EE= Elimination of errors Self-criticism eliminates bad ideas before action The real world is a filter that penalizes/eliminates entities that act on mistaken decisions or errors (i.e., Darwinian selection operates or Reality trumps belief ) TS 1 TS 2 TS m PnPn P n+1 A OnOn EE Self criticism Environmental criticism /filter Reality trumps belief D

25 Science as a social processes for formalizing and managing knowledge to make it reliable Vines, R., Hall, W.P Exploring the foundations of organizational knowledge. Kororoit Institute Working Papers No. 3.Exploring the foundations of organizational knowledge Hall, W.P., Nousala, S What is the value of peer review – some sociotechnical considerations. Second International Symposium on Peer Reviewing, ISPR 2010 June 29th - July 2nd, 2010 – Orlando, Florida, USAWhat is the value of peer review – some sociotechnical considerations

26 Vines & Hall (2011) – Building personal and explicit knowledge from real-world experience Knowledge exists at several levels of organization – Personal tacit (W2)  Personal explicit (W3) – Organizational common (W3)  Organizational Formal (W3) – Formal integrated in organizational structure/dynamics (W2) 26

27 Vines & Hall (2011) Turning individual knowledge into reliable and trustworthy organizational knowledge 27

28 Hall & Nousala (2010) - Constructing formal knowledge 28

29 Hall & Nousala (2010) - Growing and formalizing scientific, scholarly and technical knowledge Building the Body of Formal Scientific Knowledge involves cycles of knowledge building and criticism in four hierarchical levels of cognitive organization: Existential Reality (W1)  1.Personal (“I”): observe (W2)  orient  TTs  (W1) EE  (iterate) … or … (articulate & share) (W2 & W3)  2.Collaboration Group (“We”) :  assimilate (W2)  articulate  express (W3)  EE (W1)   (iterate) … or …  (submit) 3.SST Discipline Members (“Them” – mostly via W3):  peer review (EE)   (reject/revise) … or …  (publish) 4.Knowledge Society: use  … or … evolve/retract  Maintain, extend, test society’s Body of Formal Knowledge through use 29

30 Hall (unpub) - Creating & managing formal knowledge 30

31 Contributing disciplines Physics: mechanics, dynamics, thermodynamics and cybernetics – Ilya Prigogine (Nobel laureate) – non equilibrium thermodynamics – Harold J. Morowitz 1968 – “Energy Flow in Biology” – Eugene Odum 1971 – “Fundamentals of Ecology” Biology: Genetics, cytology, natural history, evolutionary biology – My own research and teaching background – S.J. Gould 2002 – “The Structure of Evolutionary Theory” Evolutionary epistemology – Popper “Objective Knowledge” – Thomas Kuhn “The Structure of Scientific Revolutions” – John Boyd 1996 – OODA Loops from “A Discourse on On Winning and Losing” Autopoiesis – Maturana & Varela “Autopoiesis and Cognition” Theories of emergent and hierarchical complexity – Herbert Simon (Nobel laureate in economics) – Stanley Salthe 1985 – “Evolving Hierarchical Systems” – Stuart Kauffman 1983 – “The Origins of Order” Cosmology, time, causation and the “adjacent possible” – George F.R. Ellis > 2006 – evolving block and, crystallizing block universes – Kauffman > 2000 – adjacent possible 31

32 Take Home Hall, W.P Physical basis for the emergence of autopoiesis, cognition and knowledge. Kororoit Institute Working Papers No. 2: 1-63.Physical basis for the emergence of autopoiesis, cognition and knowledge Vines, R., Hall, W.P Exploring the foundations of organizational knowledge. Kororoit Institute Working Papers No. 3.Exploring the foundations of organizational knowledge All claims to know are fallible Don’t accept what you are told or read uncritically Consider sources Gurus have vested interests Science works pretty well Test important claims where you can

33 Scientific thinking in the 20 th Century

34 Fundamentalism See: American Academy of Arts and Sciences' Fundamentalism Project in the Religious Movements 1998 Homepage section on fundamentalism: Fundamentalist sectarianism – Elect or chosen membership – Sharp group boundaries – Charismatic authoritarian leaders – Mandated behavioral requirements – Idealism as basis for personal and communal identity – Stress absolutism and inerrancy in their sources of revelation – Belief that truth is revealed and unified – Arcane so outsiders cannot understand communal truth – Members are part of a cosmic struggle – Reinterpret events in light of this cosmic struggle – Demonization of their opposition; – Selective in what parts of their tradition they stress – Attempt to overturn modern culture and its power. 34

35 Henry Blaskowski on Quora The central 'faith' of science is that the world exists and is observable. Everything else stems from that. It is a faith in that it is indistinguishable from the "brain in a jar"/Matrix theory of life. No, we can't prove we are not just a brain in a jar, that we are making all this up. So, if we are in that state, science is just false. But if the world exists, then science requires no faith, just observation [and a bit more].science 35

36 20 th Century Epistemology tries to explain the power of science to understand world Plato’s “justified true belief”, Vienna Circle & Logical Positivism – Truth is knowable Post WWII – Constructivism and radical constructivism Knowledge is constructed – does not/cannot “reflect” external reality – The historian Thomas Kuhn – Anti-Nazi’s Michael Polanyi Karl Popper – Popper’s “irrationalist” students Imre Lakatos P.K. Feyerabend 36

37 Problems with Logical Positivism Gettier’s Problems – Any number of confirmations does not prove the next test will be a refutation The biological impossibility to know if a claim to know is true – The brain does not perceive the world Cognition is a consequence of propagating action potentials in a neural network. Action potentials stimulated by physical perturbations to neurons – Vision does not form an image of external reality Photons are not the objects reflecting them Photons striking retina are converted into neural action potentials in primary photoreceptor cells Neurons aggregate in the retina respond to lines, brightness, changing contrast, movements A mental construction is not identical to the external reality 37

38 Constructivism Basic constructivist tenants – World is independent of human minds – “Knowledge” of the world is always a human construct – There is little point to be concerned about external reality because you cannot know what it is Social constructivism – Social relationships and interactions construct socially held perceptions of reality and knowledge. Truth is what people believe to be true Radical constructivism – Knowledge cannot be transported from one mind into another – Individual knowledge and understanding depends on personal interpretation of experience, not what "actually" occurs. 38

39 Major scientific advances 19 th Century – Darwinian theory of natural selection – Maxwell’s equations / theory of electromagnetism 20 th Century – Chromosomal/genetic theory of inheritance – Relativity – Atomic theory – Electrodynamics/unification of forces – Quantum theory – Synthetic theory of evolution – Plate tectonics All based on theoretical speculation tested in practice Prior science largely based on natural history observations 39

40 Human knowledge/dominance of the world appears to grow through time Pragmatic observation – human power over nature has grown through time Thomas Kuhn – The Structure of Scientific Revolutions (1960) – Key ideas Paradigms – World views – Disciplinary matrices – Incommensurable usages of same words Normal science Revolutions This is constructivist historical interpretation not epistemology 40

41 Time-lines for constructing knowledge from reality (animated slides explained by references below) Martin, C.P., Philp, W., Hall, W.P Temporal convergence for knowledge management. Australasian Journal of Information Systems 15(2), Temporal convergence for knowledge management Hall, W.P., Else, S., Martin, C., Philp, W Time-based frameworks for valuing knowledge: maintaining strategic knowledge. Kororoit Institute Working Papers No. 1: (OASIS Seminar Presentation, Department of Information Systems, University of Melbourne, 27 July 2007)Time-based frameworks for valuing knowledge: maintaining strategic knowledgeOASIS Seminar Presentation

42 Slide 42 Information transformations in the living entity through time World 1 Living system Cell Multicellular organism Social organisation State Perturbations Observations (data) Classification Meaning An "attractor basin" Related information Memory of history Semantic processing to form knowledge Predict, propose Intelligence World 2 Hall, W.P., Else, S., Martin, C., Philp, W Time-based frameworks for valuing knowledge: maintaining strategic knowledge. Kororoit Institute Working Papers No. 1: 1-28.Time-based frameworks for valuing knowledge: maintaining strategic knowledge (OASIS Seminar Presentation, Department of Information Systems, University of Melbourne, 27 July 2007)OASIS Seminar Presentation

43 Slide 43 Processing Paradigm (may include W3) Another view Decision Medium/ Environment Autopoietic system World State 1 Perturbation Transduction Observation Memory Classification Evaluation Synthesis Assemble Response Internal changes Effect action Effect Time World State 2 Iterate Observed internal changes World 1 World 2 Codified knowledge World 3

44 Time-based cognitive processes in observing the world to reach a goal Based on Boyd’s OODA Loop

45 From the paper

46 immutable past the world t1t1 t 1 – time of observation t2t2 t 2 – orientation & sensemaking t 4 – effect action temporal convergence calendar time “now” as it inexorably progresses through time intended future × × × divergen t divergent futures × stochastic future convergent future temporal divergence OODA t4t4 t 3 – planning & decision t3t3 Anticipating and controlling the future from now Animated slide Click to advance

47 immutable past the world t1t1 t2t2 temporal convergence calendar time intended future × × × divergent futures × stochastic future convergent future temporal divergence OODA t4t4 t3t3 Perceivable world Cognitive edge journey thus far chart: received and constructed world view that remains extant and authoritative for a single OODA cycle. perceivable world: the world that the entity can observe at t 1 in relationship to the chart. This is the external reality (W1) the entity can observe and understand in W2 (i.e., within its "cognitive edge" journey thus far: the memory of history at t 2 as constructed in W2. Memories tend to focus on prospective and retrospective associations with events (event-relative time) and can also be chronological in nature (calendar time) chart “now” as it inexorably progresses through time recent past: recent sensory data in calendar time concerning the perceivable world at t 1 (i.e., observations) the entity can project forward to construct a concept of the present situation (i.e., at t 3 ), or some future situation. Recent past is constructed in W2 based on what existed in W1 leading up to t 1. recent past Present: calendar time: when an action is executed. perceived present: the entity's constructed understanding in W2 of its situation in the world at time t 3 ; actual present: the entity's instantaneous situation in W1 at time t 4. perceived present Proximal future: the entity's anticipated future situation in the world (W2) at t 4 as a consequence of its actions at t 1+j, where j is a time-step unit—typically on completing the next OODA cycle. This anticipation is based on observed recent past, perceived present and forecasting of the future up to t 4. OODA t 1+j proximal future Intended future: the entity's intended goal or situation in the world farther in the future (at t gs, where gs is a goal- state and t gs is the moment when that goal is realised). Intentions are not necessarily time specific but are always associated with an event or goal-state (i.e., the arrival of a set point in calendar time can also be considered to be an event). t gs convergent future: the entity’s mapping of the proximal future against an intended future in which t gs can be specified. t 1 and t 1+j can also be mapped to t gs and then t gs+1 forecasted in the form of some subsequent goal. divergent future: a world state where the entity’s actions in the proximal future (t 1+j ) failed to achieve the world state of the intended future at t gs. Animated slide Click to advance


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