On Mon, Mar 16, 2015 at 9:59 AM, martin biehl via AGI <[email protected]> wrote:
> A policy is a one-step plan depending on observations/state. The > (observation dependent) two-step plan is obtained from the policy by > incorporating the next observation and performing the associated action. A > mullti-step plan is then dependent on the multiple future observations. A > plan that does not depend on future observations is a special case of this, > and maybe is what AI planning does (but I don't know much about it). > A traditional plan in the AI planning literature sense does not depend on future observations, but there is now a big literature on dynamic/adaptive planning algorithms as well... ben > > On Mon, Mar 16, 2015 at 1:33 AM, Piaget Modeler via AGI <[email protected]> > wrote: > >> >> Thanks for that feedback. Much appreciated. >> >> Any other viewpoints? >> >> Anyone... >> >> Anyone... >> >> Bueller... >> >> Bueller... >> >> ~PM >> >> ------------------------------ >> From: [email protected] >> To: [email protected] >> Subject: RE: [agi] Plans vs. Policies >> Date: Mon, 16 Mar 2015 03:13:46 +0200 >> >> >> In brief then... >> >> The example model by itself is no silver bullet. It is suggested that it >> be seamlessly integrated with 2, other quantum-based methodologies known to >> me. Recently-verified research on the potential for the 3 integration has >> proved successful. Thus, it forms a 3-body approach, which is significant >> in its holistic value. All 3 the base methodologies operate as a platform >> of synthesis in entangled and/or disentangled states of thesis and >> antithesis. By viewing it in this way, one would notice that it potentially >> offers full support for the content of your ongoing discussions on coding? >> >> In most-normal form, the ontological model already contains all the >> inherent, system policies. This is an emerging by-product of the >> engineering process. It is robust in that it has 2 hierarchies of control >> (Criticality and Priority). There are various strategies for dealing with >> the hierarchy at any level of abstraction. >> >> The inherent policies are transcribed into simple sentences, exploiting >> all the implications of the possible, compound functions (adaptive >> associations - not dependencies). Except for components of the value >> "outcome" - never present in the existentially mature ontological model as >> submitted - all other components are potentially self recursive. >> Cursiveness would probably emerge at the reductionist level. In general, >> all contexts contain their own, particular level (graining) of policies. >> These could be tweaked in terms of coarseness, and thus perspective. Scope >> of work could be managed into programs and projects, budgets, and so on. >> >> As such, the ontology presents as a superpattern, which is repeated >> consistently throughout any life cycle of any ontological event. Any >> triggering of the system would be treated as a state and an event. States >> and events would hold different values of the same, related data. Ambiguity >> becomes a non issue. This would provide elasticity to allow for dynamic >> routing within the policies of the hierarchy and scalable, parallel >> processing. A basic, optimization algorithm would come in very handy at >> this point. Policy statements may further be converted into plans, but >> these may never be in conflict with the superposition policy framework in >> the "superpattern". Thus, plans become objectively testable for ontological >> viability. >> >> Once entangled, policies assume a watchdog role. However, due to the >> nature of the entangled hierachical standard, not all policies would have >> to consume system resources at all times. Thus, policies could be created >> and destroyed for functional value, without negatively affecting the >> e-governance competency and performance. During intital systems >> development, policies would become semantically embedded into processes, >> via rules. Processes would also include functions, procedural workflow >> (program logic), and data. The value of information (views, products, and >> reports) would depend on the event-eco-systemic and end-user requirements, >> but be determined via the collective elements of process. >> >> Overall, the ontology is supported by a problem-solving framework, which >> is fully integrated with the systems-management framework. The elements of >> the problem-solving framework are People, Organization, Technology and >> Process. These elements are synthesized by its own version of an inference >> engine, namely E-Governance. For practical purposes, all policies are >> registered in the e-Governance layer, but co-managed by the actual policies >> and a policy-inference component, and so on to reduction. This layer >> provides the external ontological boundary, or People seam, to all MMI >> events. >> >> Even further, the ontology is supported by a practical, >> systems-management framework, which is driven by various aspects of system >> events, across workflow (content), including closed and open-looped >> feedback (feedback), of the emergent value chain (competency) for each >> event of the instantiation of a plan. In addition, the ontology is directly >> strenghtened by a researched, systems model for generative methodology. By >> design, all parts of the whole speak the same systems language, and when in >> synthesis, should theoretically generate the exponential value of being >> worth more than the sum of its parts. >> >> Trade-offs? So far, field research has yielded only 1, significant >> tradeoff. This tradeoff occurs during the process of migrating a systems >> model (logical) to a functional process (logical). The absence of reliable >> science for process remains an actual constraint, but some strategies for >> testing the consistency of process has been designed to deal with possible >> quality and integrity issues which may arise during the migration. >> >> Further, for AGI, I would imagine tradoffs occurring in the form of >> programming language(s), frameworks, and the selection of networked >> platform(s). In short then, one potential process tradeoff and x number of >> emerging technical tradeoffs. These tradeoffs should be dealt with as >> constraints or system requirements within the various extended >> architectures. These could probably be included as a standard model in any >> API, or API bus. To determine its suitability to the ontology, all >> architectures have to be tested for retro compliance with the policy >> implications of the superpattern. >> >> In summary: >> Within this ontology, a Plans vs Policies construct cannot exist within >> the operational system. At a planning decision level, they could exist >> separately within the same spacetime, but still not in opposition. Thye >> remain semantically separated entities in their own right. This is where >> planning could be used in a staging role, without having any direct >> performance impact on the operational system, other than >> eventually-approved workload (semantically integrated) or demand (workflow >> management) on system resources. >> >> When finally implemented (institutionalized) all polices become events of >> plans. Whn implemented (stage gated) plans become events of programs and >> projects. Projects inherit policy-compliant processes, sub-plans, special >> instructions (as problems), functions, resources, time, costs, and >> semantics. It becomes the structure for all these elements of Plan in >> Action (as a solution mechanism or value chain). In purely machine terms, >> Project could be satisfied by a single character, status parameter of any >> element within the ontology. In psuedo code; If project status = m, set >> elements {a,b,c,d...} to 0, else 1. This would auto-generate a >> mutally-exclusive construct for that particular event instance (tweakable >> via a standards-driven range and/or threshhold of graining). >> >> Control over project elements may be strengthened by a cross-correlating >> state function, which would relatively affect the mutual-exclusivity >> construct in a dynamic manner if needs be, at optimal efficiency. For >> example, if any of the excluded elements should be assigned a particular >> 1/0 workflow status, a particular rule may update the construct >> automatically, and in theory exclude/invoke another element in one step, >> and/or destroy the memory-resident element if it were not required for any >> event-future processing. Thus, resource-utilization could be pruned on a >> real-time basis, advancing the overall platform and layered performance to >> a level of effective complexity. >> >> Thank you. This was useful to me to explain. >> >> I hope it was generally clear enough and pertinent to your questions. >> >> >> From: [email protected] >> To: [email protected] >> Subject: [agi] Plans vs. Policies >> Date: Sun, 15 Mar 2015 16:22:46 -0700 >> >> Reinforcement Learning uses "policies" to select actions while most work >> in AI Planning emphasizes >> the construction and representation of a "plan" which consists of a >> sequence of actions (or a hierarchy >> of composite and primitive actions). Kindly compare, contrast, evaluate >> trade-offs, and recommend >> the plans or policies approach >> >> Your rationale is appreciated. >> >> ~PM >> >> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/26941503-0abb15dc> | >> Modify <https://www.listbox.com/member/?&;> Your Subscription >> <http://www.listbox.com> >> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/19999924-4a978ccc> | >> Modify <https://www.listbox.com/member/?&;> Your Subscription >> <http://www.listbox.com> >> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/10872673-8f99760d> | >> Modify <https://www.listbox.com/member/?&;> Your Subscription >> <http://www.listbox.com> >> > > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/212726-deec6279> | Modify > <https://www.listbox.com/member/?&;> > Your Subscription <http://www.listbox.com> > -- Ben Goertzel, PhD http://goertzel.org "The reasonable man adapts himself to the world: the unreasonable one persists in trying to adapt the world to himself. 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