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Prediction markets are powerful tools to elicit and aggregate beliefs from strategic agents. However, in current prediction markets, agents may exhaust the social welfare by competing to be the first to update the market. We initiate the study of the trade-off between how quickly information is aggregated by the market, and how much this information costs. We design markets to aggregate timely information from strategic agents to maximize social welfare. To this end, the market must incentivize agents to invest the correct amount of effort to acquire information: quickly enough to be useful, but not faster (and more expensively) than necessary. The market also must ensure that agents report their information truthfully and on time. We consider two settings: in the first, information is only valuable before a deadline; in the second, the value of information decreases as time passes. We use both theorems and simulations to demonstrate the mechanisms.
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Memory and Reward-Based Learning: A Value-Directed Remembering Perspective
The ability to prioritize valuable information is critical for the efficient use of memory in daily life. When information is important, we engage more effective encoding mechanisms that can better support retrieval. Here, we describe a dual-mechanism framework of value-directed remembering in which both strategic and automatic processes lead to differential encoding of valuable information. Strategic processes rely on metacognitive awareness of effective deep encoding strategies that allow younger and healthy older adults to selectively remember important information. In contrast, some high-value information may also be encoded automatically in the absence of intention to remember, but this may be more impaired in older age. These different mechanisms are subserved by different neural substrates, with left-hemisphere semantic processing regions active during the strategic encoding of high-value items, and automatic enhancement of encoding of high-value items may be supported by activation of midbrain dopaminergic projections to the hippocampal region.
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- Award ID(s):
- 2048692
- PAR ID:
- 10639837
- Publisher / Repository:
- Annual Reviews
- Date Published:
- Journal Name:
- Annual Review of Psychology
- Volume:
- 73
- Issue:
- 1
- ISSN:
- 0066-4308
- Page Range / eLocation ID:
- 25 to 52
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1146/annurev-psych-032921-050951
