The AXIOM approach for probabilistic and causal modeling with expert elicited inputs

Expert informants can be used as the principal information source in the modeling of socio-techno-economic systems or problems to support planning, foresight and decision-making. Such modeling is theory-driven, grounded in expert judgment and understanding, and can be contrasted with data-driven modeling approaches. Several families of approaches exist to enable expert elicited systems modeling with varying input information requirements and analytical ambitions.This paper proposes a novel modeling language and computational process, which combines aspects from various other approaches in an attempt to create a flexible and practical systems modeling approach based on expert elicitation. It is intended to have high fitness in modeling of systems that lack statistical data and exhibit low quantifiability of important system characteristics. AXIOM is positioned against Bayesian networks, cross-impact analysis, structural analysis, and morphological analysis. The modeling language and computational process are illustrated with a small example model. A software implementation is also presented.</div

Probabilistic Logics in Foresight

A prudent decision-maker facing a complicated strategic decision considers the factors relevant to the decision, gathers information about the identified factors, and attempts to formulate the best course of action based on the available information. Careful consideration of any alternative course of action might reveal that in addition to the desirable intended consequences, a number of less desirable outcomes are likely to follow as well. Facing a complicatedly entangled net of considerations, entwined positive and negative outcomes, and uncertainty, the decision-maker will attempt to organize the available information and make the decision by using some strategy of reasoning on the information. A logic is away of reasoning adherent to rules, based on structured knowledge. A modeling language and inference rules comprise a logic. The language of a logic is formal, consisting of a defined set of building blocks having well defined meanings. The decision-maker can use a modeling language to describe the information pertinent to the decision-making problem, and organize the information by giving it a structure, which specifies the relationships between the individual considerations. While reasoning about the extensive amount of information in its disorganized form may be overwhelming, in a structured form the information becomes much more useful for the decision-maker, as nowit can be analyzed in a systematic fashion. Inference is systematic reasoning about structured information. As the information is described in a formal and structured way and the process of reasoning about it is systematic, the inference may be automated. Computational inference permits reasoning that would not be possible by intuition in cases where the amount of considerations and their interdependencies exceeds human cognitive capacity. The decision-maker may direct the efforts to describing the decision factors and knowledge with the formal language, with a narrower and more manageable frame of attention, and perform the inference with a computer. Probabilistic language gives room for haziness in knowledge description, and is thus suitable for describing knowledge originating from humans, conveyed to the decision-maker in a non-formal format, such as viewpoints and opinions. Many domains of decision-making and planning use human sourced knowledge, especially if the informants are knowledgeable people or experts with relevant, developed understanding on the domain issues. The expert views can augment the knowledge bases in cases where other forms of information, such as empirical or statistical data, are lacking or completely absent, or do not capture or represent considerations important for the decision-making. This is a typical setting for strategic decision-making, long range planning, and foresight, which have to account for developments and phenomena that do not yet exist in the form they might in the future, or at all. This work discusses approaches for decision support and foresight oriented modeling of expert knowledge bases and inference based on such knowledge bases. Two novel approaches developed by the author are presented and positioned against previous work on cross-impact analysis, structural and morphological analysis, and Bayesian networks. The proposed approaches are called EXIT and AXIOM. EXIT is a conceptually simple approach for structural analysis, based on a previously unutilized computational process for discovery of higher-order influences in a structural model. The analytical output is, in relation to comparable approaches, easier to interpret considering the causal information content of the structural model. AXIOM is a versatile probabilistic logic, combining ideas of structural analysis, morphological analysis, cross-impact analysis and Bayesian belief networks. It provides outputs comparable to Bayesian networks, but has higher fitness for full model parameterization through expert elicitation. A guiding idea of the methodological development work has been that the slightly aged toolset of cross-impact analysis can be updated, improved and extended, and brought to be more interoperable with the Bayesian approach

Key Trends of Climate Change in the ASEAN Countries : The IPAT Decomposition Analysis 1980–2005

Decomposition analyses of energy consumption and CO2 emissions have mainly focused on effects of changes in economic activity, energy intensity and fuel mix, and structural changes in energy consumption in different countries or different sectors of the economy. This e-Book introduces a different perspective by identifying five globally relevant factors affecting CO2 emissions. Changes in carbon intensity of primary energy, efficiency of the energy system, energy intensity of the economy, level of economic development, and the amount of population have been identified by extending the well-known IPAT identity

Futures Horizon to Sustainability Challenges of the Lao PDR 2050 : Adaptive Foresight Thinking and New Futures Perspectives to Energy and Natural Resource Planning in the Lao People´s Democratic Republic

This e-book is focused on energy and natural resource planning in Lao PDR. The aim is to present some futures oriented analyses and discuss key planning challenges of Laos´s energy economy and natural resource use. In this e-book these questions are linked to the Adaptive Foresight methodology, that has been used as general framework in interactive and participative projects in Lao PDR

Paikallisen ruuan tulevaisuudet ja yhteiskunnalliset vaikutukset

Erilaiset vaihtoehtoiset ruokajärjestelmät haastavat hallitsevan ruokajärjestelmän. Monissa vaihtoehtoisissa järjestelmissä korostuvat tuottajan ja kuluttajan vuorovaikutus, sosiaaliset ja ympäristökysymykset sekä paikallisuus. Ruuan tuotantopaikat, tuottajat ja kuluttajat kytkeytyvät yhteen pitkään jatkuneen eriytymiskehityksen jälkeen uusilla, nykyaikaisilla tavoilla. Koska tällaiset ruokajärjestelmät yleistyvät kehittyneissä teollisuusmaissa, hallitseva ruokajärjestelmä ei ilmiselvästi tyydytä kaikkien ruokaketjun osapuolten tarpeita riittävällä tavalla. Aika näyttää, tuleeko vaihtoehtoisista järjestelmistä valtavirtaa vai jäävätkö ne ”vaihtoehtoisiksi”. Tässä raportissa on esitetty tulokset ”Paikallisen ruuan tulevaisuuskuvat ja yhteiskunnalliset vaikutukset” -hankkeesta (PARTY). Hankkeessa laadittiin kirjallisuuskatsauksen ja tulevaisuusverstaiden pohjalta tulevaisuuskuvat neljän kestävän kehityksen ulottuvuuden varaan rakentuvista paikallisista ruokajärjestelmistä: lyhyestä, vihreästä, reilusta ja aidosta ketjusta. Lyhyen ketjun mahdollisen toteutumisen keskiössä ovat toimintatavat ja ketjun valtarakenteet, Vihreän ketjun tuotekehitys, teknologia ja innovaatiot, Reilun ketjun toimijuus ja tieto sekä Aidon ketjun kulttuuri, arvostus ja tuoteosaaminen. Tulevaisuuskuvien toteutumisella olisi asiantuntija-arvioiden perusteella suurimmat vaikutukset maaseudun elinvoimaisuuden vahvistumiseen, ruokajärjestelmän sosiaalisen hyväksyttävyyden parantumiseen, aineettoman hyvinvoinnin lisääntymiseen ja ruokatuotannon kannattavuuden parantumiseen. Tulevaisuuskuvien hahmottaman ruokajärjestelmän lupaavimmat kehittämiskohteet olisivat asiantuntija-arvioiden perusteella kiertotalouden vahvistaminen, ympäristökuormitusta vähentävä tuotekehitys, paikallisen ruuan suosiminen julkisissa hankinnoissa ja ruokavalioiden muuttaminen kasvispainotteisemmiksi. Tulokset eivät ole ennusteita: ne antavat viitteitä siitä, mihin asioihin ruokajärjestelmän muutoksessa, kehittämisessä ja tutkimuksessa on syytä kiinnittää huomiota

Paikallisen ruuan tulevaisuudet ja yhteiskunnalliset vaikutukset

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