Agent-based modeling is used for simulating the actions and interactions of autonomous entities aiming to assessing their effects on the system as a whole. At an abstract level, an agent-based model (ABM) is a representation of the many simple agents and interactions among them. The decision making of the agents is based on the rules given to them. In an ABM, the model output is the result of internal decision-making and may differ with alteration in the decision path. On the contrary, with the set of rules embedded in agents, their behavior is modeled to take a ‘certain action’ in a ‘certain situation’. It suggests that the internal decision making behavior of agents is truly responsible for the model output and thus it cannot be ignored while validating ABMs. This research article focuses on the validating agents’ behavior by evaluating decision-making processes of agents. For this purpose, we propose a validation framework based on a participatory simulation game. Using this framework we engage a human player (i.e. a domain stakeholder) to allow us to collect information about choices and validate the behavior of an individual agent. A proof-of-concept game is developed for a city logistics ABM to test the framework.
Waste separation at companies is considered a priority to achieve a circular and sustainable society. This research explores behaviour change poli-cies for separating the organic fraction of municipal solid waste (OFMSW) at Small and Medium Enterprises (SMEs), particularly in cities. At SMEs, co-work-ers are responsible for waste disposal. Therefore, their behavioural intention to-wards pro-environmental action plays a major role. In this study, we have used agent-based modelling and simulation to explore the waste behaviour of the ac-tors in the system. The models were co-created in participatory workshops, sur-veys and interviews with stakeholders, domain experts and relevant actors. Ad-ditionally, we co-created and tested practical social and technical interventions with the model. We used the collaborative modelling method Lange reported to conceptualise, implement, test and validate the models. Five policies that affect waste separation behaviour were included in the model. The model and simula-tion results were cross-validated with the help of a literature study. The results were validated through experts and historical data to sketch a generalisable idea of networks with similar characteristics. These results indicate that combinations of behaviour profiles and certain policy interventions correlate with waste sepa-ration rates. In addition, individual waste separation policies are often limitedly capable of changing the behaviour in the system. The study also shows that the intention of co-workers concerning environmental behaviour can significantly impact waste separation rates. Future work will include the role of households, policies supporting separating multiple waste types, and the effect of waste sep-aration on various R-strategies.
In Eastern Africa, increasing climate variability and changing socioeconomic conditions are exacerbating the frequency and intensity of drought disasters. Droughts pose a severe threat to food security in this region, which is characterized by a large dependency on smallholder rain-fed agriculture and a low level of technological development in the food production systems. Future drought risk will be determined by the adaptation choices made by farmers, yet few drought risk models … incorporate adaptive behavior in the estimation of drought risk. Here, we present an innovative dynamic drought risk adaptation model, ADOPT, to evaluate the factors that influence adaptation decisions and the subsequent adoption of measures, and how this affects drought risk for agricultural production. ADOPT combines socio-hydrological and agent-based modeling approaches by coupling the FAO crop model AquacropOS with a behavioral model capable of simulating different adaptive behavioral theories. In this paper, we compare the protection motivation theory, which describes bounded rationality, with a business-as-usual and an economic rational adaptive behavior. The inclusion of these scenarios serves to evaluate and compare the effect of different assumptions about adaptive behavior on the evolution of drought risk over time. Applied to a semi-arid case in Kenya, ADOPT is parameterized using field data collected from 250 households in the Kitui region and discussions with local decision-makers. The results show that estimations of drought risk and the need for emergency food aid can be improved using an agent-based approach: we show that ignoring individual household characteristics leads to an underestimation of food-aid needs. Moreover, we show that the bounded rational scenario is better able to reflect historic food security, poverty levels, and crop yields. Thus, we demonstrate that the reality of complex human adaptation decisions can best be described assuming bounded rational adaptive behavior; furthermore, an agent-based approach and the choice of adaptation theory matter when quantifying risk and estimating emergency aid needs.
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