### Table 1: The significance of spotting the neural reward signal. We used several templates to verify the significance of spotting: the prototypical template, a flat template (all bins are equal), a template computed from segments aligned 2 seconds before the reward cue, and a shuffled prototypical template. This significance level was the difference between the number of detections in the original data and the average number of detections in the surrogate data. This difference was measured in standard deviation (SD) of the shuffled data.

### Table 1: The signi cance of spotting the neural reward signal. The rst column gives the animal identity and the session number. The number of simultaneously recorded TANs in each session is given in the second col- umn. We used several templates to verify the signi cance of spotting: the reward response (calculated separately for each of the recording sessions), a at PSTH, and a PSTH computed from segments aligned 2 seconds before the reward cue. A signi cance level was computed for each of these exper- iments. This level was the di erence between the number of detections in the original data and the average number of detections in the shu ed data. This di erence was measured in standard deviation (SD) of the shu ed data. Di erences greater than 3 SDs are considered as signi cant deviations from the null hypothesis.

### Table 1. Reward

"... In PAGE 4: ... 3.1 Reward based on Action and Delay The reward is given in Table1 below. For Action=takes taxi the reward is independent of the delay.... ..."

### Table 3 Reward perceptions

2003

"... In PAGE 13: ... It was found of interest to see how these two compare. Results are summarized in Table3 . Again, the scale went from 1 (1=To a little extent, 6=To a great extent).... In PAGE 14: ...Table 3 Reward perceptions The highest score in Table3 is achieved for the item that promotion of a lawyer in the firm is based on ability and how well he/she does his/her work. Hunter et al.... In PAGE 14: ... The same calculation was applied in this research to enable comparison of results. There are some interesting differences as listed in Table3 . For example, lawyers in Australian law firms seem more fairly rewarded for the amount of effort they put in than lawyers in Scottish law firms.... In PAGE 14: ...nowledge sharing attitudes and reward attitudes in law firms (Hunter et al. 2002). Relationships between attitudes can be explored by correlation analysis. In Table 4, all correlation coefficients between six knowledge-sharing attitudes from Table 2 and reward attitudes from Table3 are listed. K1 K2 K3 K4 K5 K6 R1 R2 R3 R4 R5 R6 K1 -.... ..."

Cited by 1

### Table 6: Reward functions

2001

"... In PAGE 5: ... For each case, the cost per unit time is multiplied with the expected number of tokens in the corresponding places and the total cost is computed. The reward functions used to obtain these measures are shown in Table6 . It is assumed that the cost incurred due to rejuvenation is much less than the cost of anodeorsystemfailure.... In PAGE 6: ... Therefore, there is a tradeo involved here and it is up to the user/operator on what he/she considers important. All the costs shown in Table6 are costs per unit time. In our analysis, we x the value for cost nodefail at $5,000/hr and vary the ratio cost nodefail =cost rejuv .... ..."

Cited by 20

### Table 2: The reward matrix

"... In PAGE 7: ... We will refer to a stable population norm as a stable strategy. The matrix of rewards per period to a focal individual, using a given row strat- egy against a population using a given column strategy, can now be determined from (1)-(3), (5) and (8), and is shown in Table2 . We will denoted this matrix by A, so that aIJ is the reward to an individual using strategy I against n individuals us- ing strategy J.... In PAGE 7: ... Note that the bene ts of monitoring to the focal individual are independent of the number of monitors if no one else is poaching, as indicated by the subscripted dots in columns 5 and 6 of the payoff matrix. A population strategy is stable if its diagonal element in Table2 is the largest in its column. In other words, strategy J is stable if aJJ exceeds aIJ for all I 6 = J; or equivalently, if the only non-positive term in column J of the population stability... In PAGE 11: ... The strategy NM that supports the agreement is a cooperative strategy when the reward to each individual from not hunting and monitoring exceeds the bene t to each individual from hunting (with the higher-value technology) but not moni- toring, or strategy HX. In other words, and in terms of the payoff matrix A de ned by Table2 , NM is a cooperative strategy if a55 exceeds both a22 and a44 or f ? c0 + B n + 1 gt; VH: (19) The higher the value of cH, or the lower the value of RH, the greater the sig- ni cance of whether NM is a cooperative strategy. In general, if a strategy is the only stable one, then it will ultimately emerge as the community norm; whereas if a second strategy is also stable, then the rst will emerge only if it yields a higher com- munity reward.... ..."

### Table 2. Rewards for

2005

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### Table 2: Reward System

"... In PAGE 14: ... To this end, the agent could exert torque on the first link by using the motor. The agent could finish one episode by (1) reaching the goal state and stay in it for a given time interval (see Table2 ) (2) reaching a time limit without success (3) violating predefined speed limits. After an episode the agent was restarted from a random state chosen from a smaller but frequently accessed domain of the state space.... ..."