transactions for which the total utilitarian benefit exceeds the cost. However, there are several important deviations from those assumptions in reality: 1. The miner does pay a higher cost to process the transaction than the other verifying nodes, since the extra verification time delays block propagation and thus increases the chance the block will become a stale. 2. There do exist non-mining full nodes. 3. The mining power distribution may end up radically inegalitarian in practice. 4. Speculators, political enemies and crazies whose utility function includes causing harm to the network do exist, and they can cleverly set up contracts where their cost is much lower than the cost paid by other verifying nodes. (1) provides a tendency for the miner to include fewer transactions, and (2) increases NC ; hence, these two effects at least partially cancel each other out. (3) and (4) are the major issue; to solve them we simply institute a floating cap: no block can have more operations than BLK_LIMIT_FACTOR times the long-term exponential moving average. Specifically: blk.oplimit = floor((blk.parent.oplimit \* (EMAFACTOR - 1) + floor(parent.opcount \* BLK\_LIMIT\_FACTOR)) / EMA\_FACTOR) BLK_LIMIT_FACTOR and EMA_FACTOR are constants that will be set to 65536 and 1.5 for the time being, but will likely be changed after further analysis. There is another factor disincentivizing large block sizes in Bitcoin: blocks that are large will take longer to propagate, and thus have a higher probability of becoming stales. In Ethereum, highly gas-consuming blocks can also take longer to propagate both because they are physically larger and because they take longer to process the transaction state transitions to validate. This delay disincentive is a significant consideration in Bitcoin, but less so in Ethereum because of the GHOST protocol; hence, relying on regulated block limits provides a more stable baseline. How? ↗