Read and analyze an article that uses an agent-based model, and present it to your classmates. Select an article from the list on this page (link). You are also welcome to use an article you find on your own, as long as it meets the criteria for a scientific model. 

Article critiques: Create a new thread and post a critique of an article. Your critique should be at least 300 words and should address the following questions:

1. How would you describe the model? What is it made of? What does it do?
2. What research question(s) did the authors investigate?
3. What did the researchers learn by using this model? What were their results?
4. How did the researchers make sure their model is credible? Do you think it is trustworthy enough to investigate their research question(s)?
5. Was agent-based modeling a good choice for this study, in your opinion?
6. Include a link or full citation for your source material.

Reply posts: Next, write substantive, thoughtful replies to at least two of your peers’ posts. Reply posts should address the following prompts:

• Do you agree with the assessment in the original post? If you do agree, indicate what convinced you. If you don’t agree, explain why. 
• What other research questions might be addressed by the model? 
• What other types of models might address the research aims?
• You may also share any prior knowledge or personal experience you have with the topic to enrich the discussion. 

Post 1 to reply: 

Filatova, Olga A., and Patrick J. O. Miller. 2015. “An Agent-Based Model of Dialect Evolution in Killer Whales.” Journal of Theoretical Biology 373 (May): 82–91. https://doi.org/10.1016/j.jtbi.2015.03.020.

Killer whales are a unique animal species in that they have vocal dialects that they learn from other whales. A group of orcas living around the San Juan Islands can sound different than a pod off the coast of Mexico. Whales can learn and replicate sounds they encounter from other whales. In this article, the researchers describe an agent-based model of orca populations and test a set of vocal-learning rules to evaluate which mechanism might lead to the development of dialect groupings seen in the whale’s native habitat. They tested a null model with genetic transmission and no learning, and ten models with learning rules that vary by template source, variation type and type of call change. The model produced results that only really showed some similarity to wild orcas. A pattern like the dialect diversity seen in the wild came about only when rules were applied in combinations and similar outputs could happen from different learning rules and their combinations. What happened with the model emphasizes the lack of information on quantitative features of wild killer whale. It is because of this that it seems to me that maybe model wasn’t the best way to study this topic.

Post 2 to reply :

1. This agent-based model is studying the market penetration of plug-in hybrid electric vehicles or (PHEV). This model examines the sensitivity to gasoline prices, to accuracy in estimation of fuel costs, to agent willingness to adopt the PHEV technology, to PHEV purchase price and rebates, to PHEV battery range, and to heuristic values related to gasoline usage.  I agree this is a good model to the fact the researchers are trying to find a better way to market PHEV’s.

2. To identify interactions among potential leverage points that could inform policy and consumer access to expected lifetime fuel costs that may enhance PHEV market penetration. How such a model could be used by policy-makers and vehicle manufacturers to help prioritize investments influencing PHEV adoption.

3. Providing stickers on the PHEV that estimate lifetime fuel costs would help consumers be open to more PHEV’s. Influencing consumers to place more weight on non-financial considerations that encourage lower gasoline consumption when making a vehicle purchase. That the current temporary $2500-$7500 PHEV federal tax credit currently offered is not likely to have lasting effects on long term fuel efficiency of the fleet unless manufacturers are able to lower sticker prices after the rebates are discontinued.  

4. This model was compared to two other similar models Diamond (2009) and Morrow et al. (2010) and compared the findings. The findings were all similar. This showed the model to be trustworthy for the most part. It should be noted the author of this model stated that further research needed to be done to gain further data and knowledge to determine PHEV technology to be willing to consider becoming new adopters.

5. This was a good use of an agent-based model. Marketing is quite complex, especially in the automotive sector. Automobile manufactures have to consistently evolve with ever-changing regulations and consumer personal preferences. Consumers while having more information readily available, often have a tough choice of buying an automobile. For most purchasing and owning an automobile is very expensive. PHEVs are fairly new to the market and most consumers look at the initial cost and savings. Using an agent-based model in this may help consumers make better-informed decisions for long term ownership as well as help manufacturers build a better-suited product. 

6. https://www-sciencedirect-com.proxy.lib.pdx.edu/science/article/pii/S0301421511002904

Please Keep reply in a different section than the discussion post section.